Chapter 1

Introduction

1.1 Need for Direction Finder (DF)

Indian army has been involved in Low Intensity Conflict

Operations/Counter Insurgency Operations in various parts of the country since past 20

years. Over the years, owing to technological advancement in various fields,

equipments being used by Anti-National Elements/Insurgents have undergone a

dramatic change. To maintain a constant edge, armed forces have also been equipping

the field army with state of art weapons and electronic equipments. Radio Direction

finders has been one such equipment being purchased of the shelf from the world

market. This equipment has proved to be a very effective Force Multiplier in the hands

of field army and is being effectively employed to monitor and detect hostile

transmission being undertaken by ANEs.

Direction Finder is a device for finding the direction to a radio source. Due

to radio's ability to travel very long distances and "over the horizon", it makes a

particularly good navigation system for ships, small boats, and aircraft that might be

some distance from their destination. This can refer to radio or other forms of wireless

communication. By combining the direction information from two or more suitably

spaced receivers (or a single mobile receiver), the source of a transmission may be

located in space via triangulation method.

1.2 Project Goal

This Project envisages carrying out a detailed study of various Direction

Finding Techniques prevalent. Detailed analysis of various parameters which influence

the system design of a Direction Finder (DF) system will then be carried out.

Thereafter, a comparison of different DF techniques, then the best amongst the all will

be utilised to develop the prototype, which may form a start point for any further

development of an indigenous DF system. Before this project is concluded, reference

will be made to current Trends in DF systems to include development work being

undertaken by DRDO, DLRL and trends in the world market.

1.3 Method of Data Collection

The primary source of data collection has been through books, periodicals

and articles. An attempt was made to tap some material on the internet and relevant

issues have been included in the text. A reference of sources has been appended at the

end of this report. An interaction with other agencies viz BEL, MAG No 5, Sig Gp

Wksps, Directorate of EME (Electronics) was also carried out to collect relevant info

on the subject.

1.4 Organization of the report

Chapter 2 of the report deals with brief overview on historical background

of DF technology. This chapter covers brief description of the different DF techniques

and a comparative analysis between the main DF technologies. At the end of this

chapter a brief on the principle of Interferometry has been covered which has been

utilised for designing of DF system.

Chapter 3 focuses on a general DF system. It gives out the major application

areas for DF system. It gives an overview of the requirements to be kept in mind while

designing the DF system. At the end it discusses the basic building blocks of DF

system and gives out separately the main requirements of the basic blocks like Antenna

system, Receiver system etc.

Chapter 4 deals in detail with the proposed DF system and also gives out a

flowchart which tells about the DF algorithm used in the proposed system. This chapter

also discusses the individual modules design, development, simulation results and test

results in the proposed system.

Chapter 5 shall describe the complete system in an integrated mode. The

entire hardware and software overview has been described vividly. It also discusses the

mathematical model of the DF algorithm used for this prototype and at last it discusses

the results obtained during the project.

Chapter 6 deals with the advance DF algorithm for multiple signal

classification. The complete details of Music algorithm including the mathematical

model and simulation results have been described. A short overview of range

calculation is also presented along with simulation results for three DF base systems.

Chapter 7 finally summarises the complete project work. The chapter also

presents improvements which can be incorporated in future designs. The entire work

has been finally concluded.

2

Chapter 2

Overview of DF

2.1 Historical Background

Radio direction finding is nearly as old as radio itself. The earliest

commercially manufactured DF systems were built in Great Britain just after the turn of

the century when vacuum tubes became commercially available as radio frequency

amplification devices[1],[2]. These early systems generally employed two or more bi-

directional loop antenna arrays. Their outputs were then amplified and fed to the

deflection coils of a “goniometer” (a typical goniometer was a two- or three-phase

mechanical resolver that employed an electromagnetically-driven pointer). A prominent

DF system employed in those early years was the Bellini-Tosi system, followed

somewhat later by the Watson-Watt “twin-channel” system [2] (named after its

inventor Sir R. A. Watson-Watt of Great Britain, who is perhaps better remembered for

his key role in the development of the early British radar technology that proved so

decisive in the Battle of Britain in 1940).

Loop-based DF systems were used for many years, but suffered from what

was known as the “night-effect” [3]. Although these systems worked reasonably well

for vertically-polarized signals during daylight hours, the horizontally-polarized signal

components received at night as a result of skywave reception (which did not occur at

these low frequencies during daylight hours) resulted in very erratic and unreliable

bearings.

This problem was solved by Adcock, an Englishman who developed and

patented (British Patent No. 130490) the Adcock DF antenna in 1919 [2],[3].

Essentially, the Adcock antenna relied upon suitably spaced difference-phased vertical

elements (aerials) to obtain the desired bidirectional antenna gain pattern with circular

lobes. Since these vertical elements could be made nearly immune to the effects of

horizontally-polarized signal components, good bearings could be obtained even on

skywave signals. The invention of the Adcock DF Antenna was a major breakthrough

in DF technology.

Watson-Watt DF systems further improved in tandem with the rapid

improvement of radio technology in general after World War I [4]. When cathode ray

tubes became available, CRTs eventually replaced the mechanical pointer displays used

until that time (at least in the more sophisticated systems). The incorporation of the

3

real-time polar CRT bearing display was another major breakthrough in DF

technology, since the CRT trace length allowed the DF operator to much more easily

discriminate between desired legitimate signals and undesired noise and multi-path.

Both single- and multi-channel Watson-Watt DF systems were built during this time,

some operating at frequencies well into the VHF range.

Doppler and pseudo-Doppler DF systems did not come into prominence

until after World War II. The concept was first formally introduced in a 1947 paper

written by Earp and Godfrey of Standard Telephones & Cables, Ltd. (a then-prominent

British DF company). Pseudo- Dopplers are actually special single-channel

implementations of interferometer DF systems (multi-channel interferometers did exist

before World War II) [2], [5]. The primary advantage of the pseudo-Doppler over the

Adcock cited by that paper was the ability of the pseudo-Doppler antenna to be

implemented as a wide-aperture device capable of reducing site errors induced by

multi-path reception. With the passage of over 50 years, many studies have been

carried out to establish ascendancy of each of the above mentioned technique over the

other but discussion has always proved to be non conclusive. Analogy of the above can

be established while trying to compare CDMA technology with GSM technology.

However an attempt has been made in later part of the study report to compares these

two technologies.

2.2 DF Technology

In the most general sense, all non-rotating radio direction finding systems

employ a DF antenna having an array of spatially-displaced aerials (also referred to as

“elements”, three or more being required for non-ambiguous operation) that are

illuminated by the received wavefront [2]. The resulting output voltages produced by

these aerials exhibit characteristics (phase, amplitude, or both) that are then measured.

Since these characteristics are unique for every received azimuth in a properly designed

DF antenna, the wavefront angle-of-arrival (bearing) can be ascertained by

appropriately processing and analyzing the aerial output voltages.

To be somewhat more specific, modern non-rotating DF systems tend to fall

into one of two broad categories. In phase-comparison DF systems [4][5], three or more

aerials are configured in such a fashion that the relative phases of their output voltages

are unique for every wavefront angle-of-arrival. Bearings can then be computed by

4

appropriately analyzing the relative phases of these output voltages. Phase-comparison

DF systems include pseudo-Dopplers and interferometers.

In amplitude-comparison DF systems [3], [5], two or more directive antenna

arrays are configured in such a fashion that the relative amplitudes of their outputs are

unique for every wavefront angle-of-arrival. Bearings can then be computed by

appropriately analyzing the relative amplitudes of these output voltages. Amplitude-

comparison DF systems include Watson- Watts and Wullenwebers.

Although there are many different DF techniques available to the DF system

designer, the only two that are truly capable of meeting the minimum performance

requirements of a truly professional-quality DF system at low- to-moderate cost are the

single-channel Adcock/Watson-Watt and pseudo-Doppler techniques (when properly

implemented).

2.2.1 Watson-Watt DF Technique

The Watson-Watt DF technique falls into the amplitude-comparison DF

technique category [2], [3]. A basic single-channel Watson-Watt DF system is

illustrated in block diagram form in Figure 2.1 below.

A standard Watson-Watt DF system [3] employs either Adcock or loop DF

antennas, with Adcock usually preferred because of their superior performance.

Actually, the DF antenna is really an array of three or more separate but co-located

antennas. Referring to a 4-aerial Adcock configuration, the first of these antennas is the

N-S bi-directional array comprising the north and south aerials. As illustrated in Figure

2.2 below, the resulting figure-of eight azimuthal gain patterns consists of circular

lobes with maximum sensitivity to the north and south and nulls to the east and west.

5

DFANTENNA

DFRECEIVER

DF BEARINGPROCESSOR

DF BEARING DISPLAY

Fig. 2.1 Functional block diagram Watson Watt DF

This figure-of-eight gain pattern is obtained by applying the N and S aerial voltages to

a differencing network that vectorially subtracts them (N-S) to produce what will

ultimately become the “Y-axis” voltage.

The second of these antennas is the E-W bi-directional array comprising the

east and west aerials. Again as illustrated in Figure 2.1, its azimuthal gain pattern is

identical to that of the NS bi-directional array, but perpendicularly oriented (as a

consequence of the fact that the two arrays are physically at right angles to each other).

This pattern is again obtained by applying the E and W aerial voltages to a differencing

network that vectorially subtracts them (E-W) to produce what will ultimately become

the “X-axis” voltage. The fig 2.3 below shows how these aerials are placed in an array.

Fig. 2.3 Adcock antenna and distribution network

6

N-S

E-W

SENSE

Fig. 2.2 Adcock DF antenna Azimuthal Gain Pattern

The third of these antennas is the omni-directional sense antenna [6]. This

omni-directional sense azimuthal gain pattern is also illustrated in Figure 3.2. The sense

antenna is required to resolve a 180° ambiguity that would otherwise result. Since the

Watson-Watt DF technique falls into the amplitude-comparison category as discussed

above, the purpose of the remaining elements of the DF system (i.e., the DF receiver,

DF bearing processor, and DF bearing display) is simply to measure the X- and Y-axis

voltages and then compute and display the bearing. As mentioned above in amplitude-

comparison DF systems, the relative amplitudes of these two voltages are unique for

every wave front angle-of-arrival. They can therefore be “mapped” into a

corresponding bearing using an appropriate algorithm that performs a computation

based on their ratio.

In order to produce the DOA estimate, the voltage output from both antenna

pairs of Adcock antenna is compared [3]. The same can be expressed:

Where d is the spacing between antenna elements. As the spacing is much

less then half a wavelength at the frequency of the signal of interest, the above equation

can be simplified to:

The north-south pair can be treated as generating the y-axis voltage while

the east-west pair creates the x-axis voltage for the array’s coordinate system. This

operation essentially uses the two voltage measurements to locate a point in an

abstracted plane, the angle of this point corresponding to the DOA of the received

signal. The arctangent of the quotient of the north-south voltage and east-west voltage

can be expressed as:

7

(2.1)

(2.2)

(2.4)

(2.3)

2.2.2 The Pseudo-Doppler DF Technique

The Doppler and derivative Pseudo-Doppler algorithms are single-channel

algorithms that produce a AOA estimate based on phase of the received signal [7].

Originally, the Doppler method used a single antenna that moved about the

circumference of a circle at a fixed angular velocity as shown below in fig 3.4.

Fig. 2.4 Basics of Doppler Principle

The Pseudo-Doppler method [8] was developed using a multi-element

circular array with a commutating switch that selects the antennas sequentially around

the circle to approximate the circular motion of the Doppler antenna as shown below in

figure 3.5. This algorithm seeks to measure the Doppler shift induced on the received

signal due to either the rotation of the single antenna or commutation of the switched

antenna array. The received signal is modeled as:

8

(2.5)

(2.6)

Where is the inverse of the time taken to sample around the entire antenna

array. The Doppler shift imposed on the signal will be directly proportional to the rate

of sampling around the array. When the sampling approaches the AOA of signal of

interest as well as 180 degree away, the measured Doppler shift will cross zero. If the

array is sampled at 90 or 270 degree from true AOA then measured Doppler shift will

be at a negative and positive maximum respectively.

Therefore, the DOA estimation function can consist of a simple FM

demodulator consisting of frequency discriminator followed by a zero crossing detector

as shown above. The phase of the signal at the output of zero crossing detector will be

directly proportional to the DOA. One of the major drawbacks to this system is

decreased listen-through capability due to FM and AM artifacts in the signal due to

sampling.

2.3 Comparative Analysis

2.3.1 Pseudo-Doppler DF Technique

The primary comparative advantages of the pseudo-Doppler DF technique

over its Watson- Watt counterpart are site error suppression, DF antenna economy, and

extended high frequency performance [3], [4], [7]. These advantages are conditional,

however, and require an evaluation of the underlying assumptions before being

accepted at face value. These advantages are described in subsequent paras.

M-ELEMENT

ARRAYRF FRONT

ENDFREQUENCY

DISCRIMINATOR

ZERO CROSSINGDETECTOR

9

Fig. 2.5 Pseudo-Doppler DF system

2.3.1.1 Site Error Suppression Site errors are fundamentally the result of

anomalous conditions at or near the DF antenna that result in various distortions in the

apparent angle-of-arrival of the received wavefront. As a result, the apparent angle-of-

arrival may be different than the true angle-of-arrival. The biggest contributors to site

errors are usually reflecting objects causing multi-path reception.

Unlike an Adcock-based Watson-Watt DF system whose maximum DF

antenna aperture (Adcock aerial pair spacing) can be no greater than 1.22 wavelengths

at the highest operating frequency, there is no theoretical limit to the aperture of a

pseudo-Doppler DF antenna. The aperture can be increased without bounds provided

that additional aerials are appropriately added (theoretically, the maximum separation

between adjacent aerials must not exceed 0.5 wavelengths at the operating frequency to

avoid ambiguity, although in practice this separation should be considerably less). A

wider aperture with more aerials permits greater wavefront averaging, which in turn

tends to average out errors caused by multi-path reception.

2.3.1.2 DF Antenna Economy

The electronic circuitry required for a pseudo-Doppler DF antenna is very

straightforward, requiring at minimum only appropriate high-frequency switches and

the necessary driver circuitry. This is in sharp contrast to a single-channel Adcock

antenna, which requires carefully balanced sum-difference hybrids, balanced

modulators, phase-matched cables, phase/gain correction networks, and very careful

and time-consuming testing. The simpler pseudo-Doppler DF antenna is thus more

easily and economically designed and manufactured.

2.3.1.3 Extended High Frequency Capability

The more complex electronic circuitry required by the Adcock DF antenna

is such that as a practical matter, it is not feasible to design a manufacturable wideband

DF antenna capable of good and consistent performance at frequencies over 1000 MHz

or so. The simplicity of the electronics associated with a pseudo-Doppler system is

such that there is no reason why a manufacturable wideband DF antenna with good

performance up to 2000 MHz or more should not be possible.

It is probably fair to say that the pseudo-Doppler’s strongest technical

advantage over its Watson-Watt counterpart is the site-error suppression capability that

can be obtained in its wide-aperture implementation.

10

2.3.2 THE WATSON-WATT DF TECHNIQUE

The Adcock-based Watson-Watt DF system [3], [4] has many significant

performance advantages over its pseudo-Doppler counterpart, particularly for mobile or

transportable DF applications where size constraints force the use of compact narrow-

aperture DF antennas. These advantages are described in subsequent paras

2.3.2.1 DF Sensitivity - In order to obtain good DF sensitivity, pseudo-Doppler

systems must employ a rather high commutation rate (in order to achieve sufficient FM

deviation for efficient FM demodulation). Since the designer’s latitude to raise the

commutation rate is limited by various other system constraints, a compromise is

required that results in reduced DF sensitivity. Since a Watson-Watt system relies on an

AM tone encoding technique (somewhat analogous to pseudo-Doppler commutation),

demodulation efficiency is unaffected by the tone frequencies (due to the inherent

nature of AM demodulation). The designer is therefore free to set the tone frequencies

to more favorably meet other system design constraints without compromising DF

sensitivity.

Pseudo-Doppler DF systems also suffer from bearing errors caused by aerial

reradiation. To avoid excessive bearing errors, it is necessary either to employ very

short (i.e., insensitive) aerials, or use resistive loading to reduce aerial re-radiation

(which also degrades sensitivity). The inherent symmetry of Adcock DF antennas is

such that aerial re-radiation causes negligible bearing error, with the result that Watson-

Watt DF systems are capable of excellent bearing accuracy even at the resonant

frequency of the aerials. Adcock DF antennas thus do not require shortened aerials or

other measures that compromise sensitivity to preserve bearing accuracy.

2.3.2.2 Bearing Accuracy - As mentioned in the discussion of DF sensitivity

above, pseudo-Doppler DF systems suffer from bearing errors induced by aerial re-

radiation. Recalling that the pseudo-Doppler DF system ascertains the apparent

wavefront angle-of-arrival by examining the relative phase of the aerial output voltages,

it is not difficult to visualize how inter-aerial shadowing and re-radiation can result in

phase perturbations that degrade bearing accuracy. In fact, pseudo-Doppler DF systems

almost invariably trade-off significant bearing accuracy to help mitigate the loss in

11

sensitivity. Adcock DF antennas, in sharp contrast, do not suffer from this problem and

therefore require no such trade-off.

2.3.2.3 Listen-Through Capability - In many DF applications, it is important that

the operator be able to monitor signal audio as well as obtain a line-of-bearing. The

ability of a DF system to simultaneously perform these two functions is known as its

“listen-through” capability. The general problem with single-channel DF systems is

that the modulation technique employed in the DF antenna to facilitate the DF process

(i.e., commutation or axis tone encoding) can interfere with voice or other modulation

that may reside on the received signal. This problem is very serious in pseudo-Doppler

DF systems, which are well-known for their “commutation noise”. As mentioned, the

commutation rate needs to be high to obtain good DF sensitivity, which places it in the

voice audio range. FM voice audio is therefore badly distorted (recalling that the

commutation process creates FM modulation at the commutation rate). AM audio

usually sounds equally bad as a consequence of the fact that the soft-commutation

aerial switches also impart AM modulation to the received signal as well as FM. Most

pseudo-Doppler DF systems require that the operator disable DF antenna commutation

(and thus DF capability) in order to obtain audio listen-through capability. The Watson-

Watt DF technique, in sharp contrast, provides far better listen-through capability.

2.3.2.4 Vulnerability To Resident Signal Modulation - Another general problem

with single channel DF systems is their potential vulnerability to bearing interference

caused by resident modulation on the received signal. In a pseudo-Doppler DF system,

for example, signal modulation components falling on the commutation frequency

“confuse” DF bearing processor. In a Watson-Watt DF system, a similar problem

occurs if resident signal modulation falls on either of the axis encoding tone

frequencies. In both cases, bearing “jitter” results.

The problem is especially serious for pseudo-Doppler DF systems for two

reasons [4]. First, these systems typically employ high commutation rates (to improve

DF sensitivity) that fall in the voice frequency range. Voice modulation therefore

causes interference. Second, voice modulation in the VHF/UHF range is mostly FM.

Since the pseudo- Doppler DF technique is also essentially FM in nature, it is highly

vulnerable to such interference.

12

Watson-Watt DF systems handle the bearing interference problem much

better, again for two reasons. First, the axis tone encoding frequencies are normally

well below 250 Hz, thus placing them well below the voice frequency range where they

are less subject to interference. Second, since the Watson-Watt technique relies on AM

(rather than FM) DF antenna tone encoding, the bearing interference problem is further

reduced by the fact that the preponderant voice modulation technique at VHF/UHF is

FM rather than AM.

2.4 INTERFEROMETRY

The Interferometry DF [1], [9] determines the angle of incidence of a wave by

directly measuring the phase difference between the signals picked up at different

points on the received wavefront by the elements of antenna array as shown below in

figure 3.6.

Fig. 2.6 Base line Interferometry

Unambiguous determination of the azimuth with the aid of three antenna

elements is only possible if the spacing between the antennas is not greater then half a

wavelength. In practice, the 3-antenna configuration is usually enhanced by further

antenna elements so that the antenna spacing can be optimally adapted to the operating

frequency range and it also increases the accuracy of small-aperture DF systems.

Triangular arrays are usually restricted to frequencies below 30 MHz. At higher

frequencies it is recommended to use circular arrays since these ensure the following:

(a) Equal radiation coupling between the antenna elements.

(b) Minimum coupling with the antenna supporting mast.

13

(c) Direction-independent characteristics at different positions due to the

symmetry about the center point.

2.4.1 Mathematics of Interferometry [1] Interferometers are considered as

specific cases of array antennas. The linear array in which all antenna elements lie in a

straight line at equal spacing, with DOA estimation done by the phase shift network.

The same concept can be extended to circular array which covers 360 degree of

azimuth from an mounted at one point. A single baseline of two antenna interferometer

has been shown in fig 3.7 utilized to derive the phase difference equation and show the

operation in first quadrant.

The voltage received by antenna 2 is expressed in exponential form as follows:

Where

V = the initial transmitted signal amplitude

X = the distance traveled

= free space propagation constant

Antenna 1 the voltage will be:

cosD

D

X

X

INPUT

SIGNAL

2

2

ANT

V1

1

ANT

V

14

Fig. 2.7 Interferometry principle

(2.7)

(2.8)

Where Represents the additional path length to antenna 1 as referenced to

antenna 2. Assume ( ) X to be reference zero at antenna 2 then:

Taking natural on both sides and then subtracting we obtain:

Let be defined as this difference or the real part of above equation then:

This above equation can be solved and AOA can be

expressed in terms of frequency:

where = the phase difference in radians

= the frequency in GHz

= the spacing measured in cm

= the angle of arrival

2.4.2 Correlative Interferometry

In this section of the Project report a brief overview of Correlative

Interferometry direction finding technique is presented which will be utilised to

develop the prototype DF station. The basic principle of the correlative interferometer

[9], [10] entails a comparison of the measured phase differences with those obtained for

a DF system of known configuration at given wave angle. The comparison is done

either by calculating the quadratic error or forming the correlation coefficient of the

two data sets. If different azimuth values of the comparison data set are used, the

15

(2.9)

(2.10)

(2.11)

(2.12)

(2.13)

bearing is obtained from the data for which the correlation is at a maximum. This

procedure is better explained using a figure given below:

Figure 2.8 illustrates correlation by the example of a 5-element antenna

circular array. Each column of the lower data matrix corresponds to a wave angle α and

forms a comparison vector. The elements of the comparison vectors represent the

expected phase differences between the antenna elements for this direction of

incidence. The upper 5x1 data matrix contains the currently measured phase differences

(measurement vector). To determine the unknown direction of incidence, each column

of the lower reference matrix is correlated with the measurement vector by multiplying

and adding the vectors element by element. The result is the correlation function K (α),

which reaches its maximum with the optimum coincidence of comparison vector and

measurement vector. The angle associated with the comparison vector is the wanted

bearing.

All DF techniques have both strong and weak points, and it is important that

users understand these comparative advantages and disadvantages and weigh them

appropriately for their intended application.

16

Fig. 2.8 Principle of Correlation Evaluation

The pseudo-Doppler is certainly the best known and most widely used DF

technique, its major technical strength is its site-error suppression capability when

implemented as a wide aperture fixed-site DF system. The probable explanation for this

pseudo-Doppler dichotomy is twofold, first the simplicity of the pseudo-Doppler DF

technique and second, the extended frequency of operation. The correlative

Interferometry DF algorithm has the advantage of site error suppression as we can

calculate error respective to the site and the same can be incorporated in the system.

Even design of the antenna system is also simpler as compare to amplitude comparison

DF system and its frequency range can also be extended based on the practical

requirement. The DF system which will be designed will be based on correlative

interferometry algorithm.

CHAPTER 3

DESIGN CONSIDERATIONS FOR DF SYSTEMS

17

3.1 Radio Direction-Finding Systems

A radio direction-finding (DF) system is basically an antenna-receiver

combination arranged to determine the azimuth of a distant transmitter [5]. In practice,

however, the objective of most DF systems is to determine the location of the

transmitter. Virtually all DF systems derive emitter location from an initial

determination of the arrival angle of the received signal. The determination of emitter

location by using azimuth angles measured at two or more DF systems is known as

Triangulation.

Fig. 3.1 Essential Components of a RDF System

3.2 Applications of Direction-Finding Systems

There are three principal applications for DF systems [5] which influence

the details of their design:-

(a) DF systems that are designed to determine the unknown location

of an emitter. Such systems may be fixed or movable.

(b) Navigation systems designed to determine the location of

the DF system itself with respect to emitters of known location.

(c) Homing systems that are designed to guide a vehicle carrying a DF

system toward an emitter which may be either a beacon of known

location or an emitter of unknown location.

3.3 Direction-Finding System Planning

Planning a DF system [2], [5] (which may comprise a single station or a

network of stations) must take into account a number of factors of major importance:-

18

RECEIVING SYSTEM

DF PROCESSOR

OUTPUT DEVICE

(a) Geographic area in which the emitters are located in relation to the DF

stations.

(b) Frequencies of the emitters.

(c) Number of DF stations necessary to ensure adequate accuracy of

measurement.

(d) Response time (the minimum time in which a measurement must or

can be made).

(e) Physical limitations of the system. These may include the space

available for antennas, the need (or not) for a movable system, and

limitations on equipment size, weight, and complexity.

3.4 System Approach to Direction Finding

The essential components of any DF system are shown in Fig 5.1 they

comprise of:-

(a) An antenna system to collect energy from the arriving signal.

(b) A receiving system to measure the response of the antenna system to the

arriving signal.

(c) A processor to derive the required DF information (for example,

azimuth and elevation angles and emitter location) from the output of the

receiver.

(d) An output device to present the required DF information in a form

convenient to the user.

DF ANTENNA

Fig. 3.2 Essential Components of a DF System

19

3.4.1 Direction Finding Antenna Arrays In general, a DF antenna [6], [11]

is an array of individual antenna elements arranged to provide the responses required

by the particular system. The antenna elements and arrays are of standard types that are

used in other radio-communications applications. Most of the reported algorithms are

based on the uniform linear array (ULA) and uniform rectangular array (URA)

architectures as shown below in fig 5.2.

Fig. 3.3 ULA & URA

Factors to be considered in the selection of antenna arrays [5], [6], [11] are:-

1. Coverage (the range and azimuth sector over which the target emitters

are located). This will determine the form of the array.

2. Expected propagation modes of the arriving signals. These will

determine the required elevation response of the antenna array and the type

of antenna elements to be used.

3. Combination of measurement speed and measurement accuracy. These

will determine the required aperture of the antenna array.

4. Physical requirements of the DF system (fixed or movable). These will

affect the physical form of the elements and the size of the array.

20

3.4.2 Receivers They comprise the measuring equipment of a DF system.

They are used as RF voltmeters to measure antenna responses and to provide responses

to the DF processor [12], [13]. In systems in which the azimuth angle is determined by

observation of a null or a beam maximum, a single receiver can be used, since the

processor will require only information concerning the amplitude of the response

pattern of the antenna system. However, in any system in which measurement is based

on an amplitude and / or phase comparison, a number of alternative receiver

arrangements are possible. (Fig: 3.4(a) & (b))

Fig. 3.4(a) Single channel Receiver Configuration

21

SWITCH

ANTENNA ANTENNA

SINGLE CHANNEL RECEIVER

TO DF PROCESSOR

ANTENNA ANTENNA

N - CHANNEL RECEIVER

Fig. 3.4 (b) N-channel Receiver Configuration

ANTENNA

TO DF PROCESSOR

Dual-channel and multi-channel receivers are usually arranged to operate

from a common frequency-synthesizer source, so that the phases of the output signals

will be in the same relationship as the phases of the incoming signals. Dual-channel

and multi-channel receivers may also be matched in gain and/or phase. Alternatively,

they may be made gain-and phase-stable over their measurement bandwidth and their

relative gain and phase normalized for each measurement.

3.4.3 Direction-Finding Processor The function of the processor is to

calculate the required DF and emitter location on the basis of the signal voltages at the

output of the receiver system. The complexity of processor varies with nature of the

calculations required to reduce emitter location. At the one extreme, the processor may

be as simple as an angle scale on a rotating loop. At the other extreme, a digital

processor such as in a multiport WFA system may be required. Processors for WFA

systems usually consist of small digital computers having sufficient speed and memory

for their applications. The software for such systems is usually modular, so that a

variety of antenna systems can be accommodated and optional capabilities such as

networking, signal acquisition, and signal monitoring can be provided.

3.4.4 Output Display Arrangements The purpose of output-display equipment

is to provide the required DF information in a form suitable to the user.

22

Fig. 3.5 Computer-Emulated DF Bearing Display

CHAPTER 4

DF SYSTEM DESIGN AND RESULTS

4.1 Proposed DF System

It is based on Correlative Interferometry principle [9], [15]. The block

diagram of prototype DF system is shown in figure 6.1. The system is developed in

module form i.e. all the modules like antenna system, power divider, phase detector,

filter and DF processor are developed separately and then integrated. The simulation

and experimental results of the modules developed during the first stage are given in

subsequent paragraphs.

23

Fig. 4.1 Prototype DF system

The DF system employs three omni directional antennas (monopoles) and

the output of the each antenna is given to a separate power divider through a band pass

filter. The output of power divider is then given to phase detector as shown in fig 4.1.

4.2 Proposed DF Algorithm

The flow chart of the DF algorithm which will be developed during the

second stage is given below in figure 4.2.

FILTER2.4 -2.5 GHz

FILTER2.4 -2.5 GHz

FILTER2.4 -2.5 GHz

2- WAY POWER DIVIDER

2- WAY POWER DIVIDER

2- WAY POWER DIVIDER

PHASEDETECTOR

PHASEDETECTOR

PHASEDETECTOR

DF PROCESSOR

DF ANTENNA

PROTOTYPE DF SYSTEM(BASED ON CORRELATIVE INTERFEROMETRY)

DISPLAY

AMPLIFIER

24

Fig. 4.2 Flow chart of DF algorithm

The DF algorithm shown above has to be implemented in two phases. First

phase deals with making of lookup table. In this phase the signal source is kept in the

known direction and corresponding phase data is measured and stored and then the

source is rotated for all 360 degrees and the data is stored. This process is repeated at

different time and location and finally the lookup table is developed after averaging all

the readings. Once the lookup table is developed, the test phase starts. During this

phase the source is placed in any direction randomly and again the phase differences

are measured and the correlated with the lookup table data and where maximum

correlation is found, corresponding DOA is given as output.

This same algorithm can also include method of interpolation so that the DF

accuracy can be increased based on requirement. The method of interpolation has been

discussed in depth in next chapter.

4.3 Experimental Results

25

F L OW C HAR T F OR DF AL G OR IT HM

START

PLACE TRANSMITTER

AT 00

MEASURE VOLTAGE O/POF PHASE DETECTOR

CONVERT THE VOLTAGEINTO DEGREE USINGCALIBRATION TABLE

STORE THE PHASEGIVE NAME 0 DEGREE

INCREMENT THE DIRECTION BY 1 DEGREE

ISDIRECTION

360 ?

NO

DF IS READY

YES

PLACE TRANSMITTERIN ANY DIRECTION

MEASURE VOLTAGE O/POF PHASE DETECTOR

CONVERT THE VOLTAGEINTO DEGREE USINGCALIBRATION TABLE

CORRELATE THE PHASE

WITH 00 STORED DATA

INCREMENT THE NAME BY 1 DEGREE

NAME OF MAX CORRELATIONDATA IS DOA

STOP

4.3.1 Antenna system design A uniform circular array (UCA) which provides

360 degree azimuthal coverage has been designed and fabricated for this project and

steps under taken in the designing and various result are as under:

(a) Theoretically a monopole antenna was designed which will act as each

element in the UCA. The design equation is as given below

This equation is valid for infinite ground plane and hence when the

monopole is placed in a UCA along with the finite ground plane then

optimization is required to be done to get desired results.

Optimization formula is straight forward and is as given below:

(b) Theoretical design was then simulated on IE3D software. Basically all

three antennas were simulated together in a UCA as shown below and also

the radiation pattern is given below in figure 6.4 & 6.5. The antenna was

fabricated and then tested on network analyzer.

26

where

Fig. 4.3 Monopole antenna

(6.1)

(6.2)

Top View

3-D side view

27

Fig 4.4 DF antenna system along with finite ground plane

Fig 4.5 Radiation pattern when all three monopoles are excited

Individual monopole antenna and the circular array of antenna were then

tested on network analyzer and the results are as given below.

Fig 4.6 Result

for

individual

monopole

antenna

28

Fig 4.7 Antenna testing on Network analyzer

29

Fig 4.8 Result of Monopole antenna in UCA after optimization

4.3.2 Phase detector design

30

Phase detector module is designed using IC AD 8302 [Data Sheet Attached]

which is a fully integrated system for measuring gain and phase in numerous receive,

transmit and instrumentation application. The AD8302 comprises a closely matched

pair of demodulating logarithmic amplifiers, each having a 60 dB measurement range.

The AD8302 includes a phase detector of the multiplier type, but with precise phase

balance driven by the fully limited signals appearing at the outputs of the two

logarithmic amplifiers. Thus, the phase accuracy measurement is independent of signal

level over a wide range.

(a) Phase detector module circuit diagram is shown in Figure 4.9

Fig. 4.9 Basic connection of Phase Detector module

(b) PCB design of phase detector module was done using Eagle software and is shown in Figure 4.10.

Fig. 4.10 PCB Phase Detector module

(c) Phase Detector module was tested using RF transmitter as shown in figure 4.11

31

Fig. 4.11 Phase Detector module testing

4.3.3 Power divider design Wilkinson power divider [14] model has been

utilized to design the equal split power divider to divide the antenna output and feed it

to the phase detector module. Circuit configuration of N-way Wilkinson power divider

is as shown below in fig 4.12. The N-way Wilkinson power divider/combiner provides

matching of all ports, low loss and high isolation between input and output ports due to

additional ballast resistors.

(a) The Wilkinson power divider for 2.45 GHz was designed and

simulated using IE3d software. The diagram (not to scale) and simulation

result are shown below.

32

PHASEDETECTOR MODULE

Fig. 4.12 N-way Power Divider

Fig. 4.14 S-parameter of Wilkinson power divider

4.4 Amplifier

The main functionality of the power amplifier is to amplify the output of

phase detector. The output range of the phase detector is from 30 mV to 1.8 V for 180

33

Fig 4.13 PCB of Wilkinson power divider

degree to 0 degree phase difference respectively. The amplifier increases the margin for

the ADC of Atmega 16 microcontroller by 2.47 times and this even helps in the final

correlation algorithm. The amplifier has been designed using a general purpose J-FET

quad operational amplifier TL 084 which is a low noise operational amplifier. Three

out of four amplifiers of TL 084 has been utilized in non-inverting configuration as

shown below. The value of R2 is 10k and R1 is 6.8k.

Fig. 4.15 Pin diagram – TL 084

Fig. 4.16 PCB Amplifier module

4.5 DF Processor

34

The DF processor has been designed using Atmega 16 microcontroller to

run the DF algorithm of correlative interferometry. Visha kit has been utilized to

develop a microcontroller board for Atmega 16. The main features and internal block

diagram of Atmega 16 has attached as appendix to this project report. The inbuilt ADC

of Atmega 16 has been utilized to convert the voltage output of phase detector and store

the same in the internal memory of the same microcontroller.

Fig. 4.17 Microcontroller board development

The codes develop for correlative interferometry DF algorithm was first

tested by developing a MATLAB code and feeding the details manually. Then C-code

was developed for the Atmega 16 microcontroller and the details of the complete work

have been discussed in succeeding paras. The developed microcontroller board is as

shown above. The details of the code and its implementation have been discussed in the

next chapter.

CHAPTER-5

35

ALGORITHM DEVELOPMENT

& IMPLEMENTATION

The final part of this work was concerned with the proof-of-concept

implementation of the DF algorithm discussed in previous chapter. Initially the DF

algorithm was simulated on matlab by taking readings manually and this provided the

starting point for the implementation of the algorithm on a fully integrated system. In

this chapter, we present the implementation of the algorithm including both hardware

and software platforms, the test environment, as well as the success and failures

encountered in the process.

5.1 Hardware overview

5.1.1 Antenna array

The antenna array shown in figure 5.1 is a uniform circular array of 3

monopole antennas with a diameter of approximately 12 cm. The antennas are placed in

an equilateral triangle with a phase difference of 120 degree, it is important to note the

inter antenna spacing and phase difference because if we change this data then we have

to change the lookup table accordingly. The circular array arrangement fulfills all

necessary requirements as discussed in chapter 3 and it also removes the 180 degree

ambiguity which may exist in case of linear array. Details of antenna fabrication and

testing have been discussed in chapter 4.

Fig. 5.1 Circular antenna array

5.1.2 Phase detector and amplifier module

36

The phase detector module has been developed using IC AD 8302 and the

details have been discussed in chapter 4. The output of the phase detector is a phase

internally calibrated in terms of voltage and the calibration is given in figure 5.2.

Fig. 5.2 Phase output V/s input phase difference

The phase detector unit measures gain/loss and phase up to 2.7GHz and

accurate phase measurement scaling is 10mV/degree. It operates from supply voltage of

2.7 V-5.5 V and also provides stable 1.8 V reference voltage output. The phase output

varies from 0 degree (1.8 V) to 180 degree (30mV). The developed module is shown in

figure 5.3. The output of phase detector is utilized in the voltage form itself i.e. it is not

being converted to degrees. This output is given to DF processor via amplifier unit

made using TL 084 whose design have been discussed in previous chapter.

Fig. 5.3 Phase detector module

5.2 Software Overview

37

5.2.1 Test setup

The test setup consists of a transmitter unit, receiver unit and a DF

processor. The transmitter unit is a VCO generating 2.4 GHz frequency signal and its

frequency can be varied by varying the control voltage input. Even any signal generator

or a wireless LAN module can also serves a purpose of transmitter. The receiver unit

consists of a circular antenna array, power divider, phase detector and the amplifier

unit. The DF processor consists of Atmega 16 microcontroller board and a LCD display

unit. The block diagram of complete setup is as shown below in figure----.

Fig. 5.4 DF Test setup

5.2.2 Algorithm Overview

The DF algorithm is based on correlative interferometry principle as

discussed in chapter 3. The circular antenna array is able to provide a constant phase

shift for an RF signal coming from a fixed direction and the phase shift varies as the

direction of the incoming signal is changed. As discussed in chapter 3 even this

prototype which has been developed works in the same manner, it finds out the phase

difference between various antennas for a common signal and stores that in the

processor memory. This stored data is then correlated with the lookup table data and

DOA for which it gets a maximum correlation will be displayed as direction of the

transmitter. Before we start testing we need to build up a lookup table which can work

in any environment and at any time of the day.

Actually the lookup table has to be developed in the location which is free

from EMI and even environmental radiations and for this the best suited place is an

Tx2.4GHz

PowerDivider

AntennaBase

PowerDivider

PowerDivider

PhaseDetector

PhaseDetector

PhaseDetector

Amplifier

Amplifier

Amplifier

DFPROCESSOR

LCDDisplay

38

anechoic chamber with a turntable which can rotate the DF for 360 degree and the

phase difference data can be stored in the memory as lookup table. But for this project

as we were developing a prototype with just three monopole antenna a simpler method

was adopted to develop the lookup table. Also the readings were taken only in the first

quadrant and at gap of 5 degrees. The complete system was setup in the Antenna lab

and the transmitter was moved manually. The different sets of readings were taken at

different time of the day and then averaging was done to build the lookup table and the

readings along with the lookup table is attached as appendix to this report.

The complete algorithm was simulated on matlab by loading the developed

lookup table and then feeding the phase data for the transmitter direction manually. The

matlab code of the same is attached as appendix. The system was giving 85 % accuracy

in the manual DF; this might be because of the environmental and human error.

5.2.3 Mathematical Model

The mathematical model discussed in the section 2.4 forms the basis of

development of the prototype DF system. The phase which was found taking the

natural log ratio of the two input signal, in our system it is found using the phase

detector which gives the voltage output based on the phase value and its conversion

ratio has been discussed in section 5.1.2. As we are only interested in correlating the

phase data so need of converting the voltage output of phase detector to corresponding

degrees does not arise. The lookup table which has been discussed in the pervious

section contains the voltage values of corresponding degrees and these values are then

correlated with the test data.

Let’s consider the uniform array of our system and develop the

mathematical model of the complete setup. The three monopole antennas will receive

the same signal with fixed phase difference based on there physical placement.

(5.1)

The output of the three antennas is given to power divider unit and then

given to the phase detector unit as shown in figure 5.4 and the output of phase detector

is as given below.

39

(5.2)

During the training phase this phase data is stored in the memory in the

lookup table at respective location based on the direction of training source. If it is the

test phase this data is stored in memory and correlation is performed with the lookup

table. The correlation algorithm is as given below for M directions.

(5.3)

(5.4)

(5.5)

(5.6)

The above result is based on finding the Euclidean distance between the

lookup table data and the test data and where the distance is minimum the respective

degree is the DOA of the source. The same algorithm has been simulated on matlab and

tested by manually feeding the data out from the phase detector. After testing this

algorithm on matlab, a c code has been developed for the microcontroller i.e. the DF

processor shown in figure 5.4. Both the matlab and c code are attached as appendix to

this report.

5.3 Method of Interpolation for increasing DF accuracy

Interpolation is a method of constructing new data points within the range of

discrete set of known data points. The DF algorithm which has been discussed in the

previous section refers to a lookup table for finding out correlation which means that

DOA is limited to only those degrees for which data exists in the lookup table. This

40

limitation will also give rise to reduced DF accuracy dependent on the resolution of the

lookup table. Now to remove this dependence of DF accuracy method of interpolation

has been used to provide higher resolution for our DOAs.

Interpolations are of different types like linear, polynomial, piecewise

constant, etc. Method of linear interpolation has been utilized in our DF system for

increasing the accuracy. It is the simplest method of getting values at positions in

between the data points. The points are simply joined by straight line segments and

each segment can be interpolated independently based on requirement. The method of

interpolation is required if the minimum Euclidean distance found using equation 5.5 is

not zero because if it is zero then perfect correlation and it will give out exact DOA. If

it non zero then the value and the index i.e. degree shown in equation 5.5 has been

utilized for doing interpolation.

(5.7)

The above data is required for performing linear interpolation. This data is

then fed in the equation of interpolation to find out the required degree output (DOA).

(5.8)

The method of interpolation has been implemented on matlab and the code

is attached as appendix to this report for future development.

5.3 Results Obtained

The prototype DF system which has been developed during the project can

form basis for development of a fully operational system which can be deployed in

operations. The system is able to explain the concept of correlative interferometry DF

algorithm which is being successfully implemented in this system. The following

results can be well utilized in development of first indigenized DF system.

1. The phase detector module designed using AD 8302 can be well

utilized to find out phase difference between two analog signals of

41

frequency range dc to 2.7 GHz. Other alternative can be converting the

analog signals to digital and then finding out phase difference.

2. The antenna base which has been design and developed for this

system is just for a prototype and for a small frequency band of 2.4-2.5

GHz, but in an actual system a high gain and a broad band antenna can be

utilized. Even one can also increase the number of antenna elements in the

circular array to increase the accuracy of DOA.

3. Filter units can also be utilized before the power divider so that

unwanted signals can be removed at RF stage itself. Even this will also not

affect the output of phase detector further it will not affect the DF accuracy.

4. The correlative interferometry algorithm has been tested

successfully first by simulating it on matlab and then implementing it on the

proposed DF system. The correlation between the test data and the lookup

table has been done by finding the minimum Euclidian distance; the same

can be done by some more stringent correlation algorithm based on number

of antenna elements and accuracy required.

5. The triangulation algorithm has been successfully simulated on

matlab and the same can be practically implemented once a proper three DF

base has been formed in a master-slave configuration. The simulation results

have been discussed in the chapter 6 in detail.

6. MUSIC algorithm for multiple signal classification has been

successfully simulated on matlab and have been described in the chapter 6

in detail.

42

Chapter 6

Advance DF algorithms for multiple signal classification and

Range finding

6.1 MUSIC Algorithm

The MUSIC, Multiple signal classification is a popular high resolution

technique for estimating the DOA of multiple plane waves in noisy environment, using

an array of multiple sensors. The algorithms, first proposed in 1979 by R. O. Schmidt []

falls into a class of superresolution DF algorithms. This algorithm involves eigen

decomposition of the covariance matrix derived from the input data model. The eigen

values of the covariance matrix are further divided into two sets called signal and noise

subspaces. The signal subspace consists of vectors correspond to signals received at an

array and vectors of noise subspace are completely orthogonal to the signal subspace.

The block diagram shown in figure ---- describes the algorithms in depth and same can

be summarized in as follows []:

Fig. 6.1 Music algorithm block diagram

1. Estimate the spatial covariance matrix.

2. Compute the eigenvectors in signal and noise subspaces.

3. Remove all the information about the signal subspace like power,

phase etc.

4. Find steering vectors that are orthogonal to the basis vectors for

the noise subspaces.

5. The peaks in the pseudo-spectrum will be located at the wave

numbers which corresponds to the DOAs.

43

6. The width and height of the peak does not bear any relation to any

relevant property of the signal.

6.1.1 Data model and Music algorithm

Consider a uniform linear array of M antennas (Sensors) with intersensor

spacing of d. If signal waves from different sources arrive at angles Q1, Q2… QN with

respect to the array normal, then the output of any sensor can be written as

(6.1)

In the above equation is slowly varying amplitude, w is the center

frequency of the signal, k wavenumber and is zero mean additive white complex

Gaussian noise of variance . The output of all the sensors forms a matrix Y which is

given as

(6.2)

(6.3)

where A, the steering vector, s, the signal vector and w the phase delay between two

sensors are as given below

(6.4)

(6.5)

(6.6)

It is assumed that the signal and noise are uncorrelated. The covariance

matrix of data vector would then be

(6.7)

Now carrying eigen decomposition of matrix R we can partition the signal

subspace and noise subspace eigen vector matrix which is as given below

(6.8)

44

where U and V are signal and noise subspace vectors respectively. By eigen analysis

we can represent the smallest eigen vectors as

(6.9)

at all true DOAs,

An estimate of R is obtained from N samples of data vectors as,

(6.10)

If is eigen decomposed then we would find estimate of noise subspace eigen vector

matrix but would only be an estimate hence would not be true but it will

be the minimum at true DOAs and by utilizing this fact the DOAs can be plotted using

the equation given below.

(6.11)

the above data model and result of eigen decomposition has been simulated on matlab

and the results are discussed in succeeding paras.

6.1.2 Simulation results and discussion

The music algorithm was simulated on matlab by generating the source data

and noise data and then performing eigen value decomposition, finally plotting the cost

function as given in previous section. While simulation it is assumed that each antenna

is perfectly spaced relative to other antenna in the array. But this is very difficult to

achieve when the algorithm is actually implemented even with modern construction

techniques. Suitable modification has to be done as an when required. []

The results showed in figure 6.2, 6.3 & 6.4, shows that the incoming signals

are clearly identified even as the separation between the two signals is well below the

conventional main lobe width. It is seen that if number of snapshots are less then it

increases the covariance matrix estimation error and corresponding increase in the

DOA estimation. This estimation error can be reduced by increasing number of

snapshots but speed imposes an upper limit on permissible value of N.

45

Fig. 6.2 Music spectrum with two signal sources at 20 & 60 degrees

Fig. 6.3 Music spectrum with three signal sources at 20, 60 & 100 degrees

46

Fig. 6.4 Music spectrum of two near by signal sources at 50 & 54 degrees

The simulation results of the MUSIC algorithm show the following results.

1. The capability to resolve multiple targets with separation angles

smaller then the main lobe width of the antenna array.

2. The estimation errors can be reduced by increasing the number of

snap shots, but there has to be a trade off between the speed and number of

snap shots.

3. The estimation error increases as the angle separation becomes

smaller between signals.

4. Spacing error has to be taken into account during the practical

implementation of the algorithm.

5. The number of signal sources should be less then number of

antenna elements.

6. The performance of MUSIC estimator suffers a progressive

degradation as the SNR is reduced as it causes increase in the covariance

matrix estimation error and corresponding increase in DOA estimation

error.[]

47

6.2 Range Calculation

The localization of a signal source is the primary task for most of the DF

systems. Location of the source is generally specified in terms of distances and angles

from a known reference site. Angle information i.e. DOA can be found using a single

DF system but the exact location of the signal source can only be determined by using

at least two direction finders. Bearing of the source from each DF site are plotted on a

map from the known location, to find the exact position of the source which is the

intersection of the line of bearings (LOBs). The bearings are obtained either from the

multiple, dispersed DF sites or from a single DF site moving relative to the subject

source. The coordinates of the DF locations are known before or determined relative to

bearings.

DOA estimates the location of a transmitter/source using triangulation by

measuring the angle of arrival of the received signal at two/three base stations.

Triangulation is the process of determining the location of a point by measuring angles

to it from known points at either end of a fixed baseline, rather than measuring

distances to the point directly. It is basically finding the length of one side of a triangle,

given measurements of angles and sides of the triangle formed by that point and two

other reference points.

Fig. 6.5 DF based source localization

48

DF SITE

(I)

DF SITE(II)

1 2

Area of Location

uncertainty

Figure 6.5 illustrates a location finding system composed of two direction

finders. The DOA measurement restricts the location of the source to a line. The two

DOA measurements from two DF sites are used in a triangulation process to estimate

the location of the source that lies on the intersection of these lines. If DF sites estimate

AOA perfectly (no error), the source lies exactly at the intersection point. But in

practice DF measurements always contain some error due to many factors like

sampling effects for digital DF systems, mutual coupling of antennas, multipath

propagation, site errors etc. Thus, the estimated location of the source is actually an

area of uncertainty. While only two DOA estimates are required to estimate the location

of a source, multiple DOA estimates are commonly used to improve the estimation

accuracy. Increasing the number of measurements can decrease the area of the error

region.

6.2.1 Simulation results and discussion

The localization of the source and range calculation has been simulated on

matlab and the code is attached as appendix to this report. For simulation purpose a

map of IIT Powai has been utilized for implementation of the localization algorithm.

Figure 6.6 shows the location of the DF site and source whose coordinates has been

utilized to run the algorithm.

49

DF 1

DF 3

DF 2

SOURCE 1

SOURCE 2

Area of Location uncertainty

Area of Location uncertainty

Fig. 6.5 IIT Powai Map showing DF site and source

As shown in figure 6.5 a three DF base has been form and DOA of the

source is measured. The DOA data from all DF station is then transferred to the master

DF station where the localization algorithm runs to find out the exact location and

range of the source. With two DF station exact location can only be found if the DOA

measurement is error free but practically it is not possible. Figure 6.6(a), (b) & (c)

shows both the exact localization of the source and also if DOA is not error free.

Fig. 6.6(a) Result showing exact location with two DFs with error free DOAs

50

Fig. 6.6(b) Result showing Area of uncertainty with three DF base

Fig. 6.6(c) Result showing exact location with three DFs with error free DOAs

Fig. 6.6(d) Result showing exact location of target 2 with three DFs

The above results show that DF accuracy is the most important parameter to

be kept in mind before designing a DF system. Based on operational requirement this

51

TargetTarget

parameter can be decided because higher the accuracy means higher cost, design

difficulties, etc and lower accuracy will lead to false target localization.

CHAPTER: 7

Conclusion and Future Work

7.1 Conclusions

The basic principle of Direction finders has been studied. The initial

literature survey covers the various types of DF techniques, pros and cons with

different algorithms. Due to certain disadvantages of amplitude comparison technique

such as complexity in antenna design, limited frequency range (up to 1 GHz), poor site

error suppression, and etc. phase comparison DF technique has been chosen for

implementation. The design parameters and requirements have been studied and

described briefly and the same has been used for further hardware design.

The DF system has been designed for the frequency range 2.4-2.5 GHz.

Being just a prototype the azimuth coverage is only 90 degrees and also the lookup

table has been made for 0 to 90 degree with 5 degree resolution. The modular design of

DF system has been presented in this project report which can be integrated on a single

PCB in future, based on requirement. The monitoring section has not been included in

this DF system due to paucity of time, there are various receivers available in the

market so based on the frequency requirement any receiver can form the monitoring

section of the DF system.

The DF algorithm used for the system has been tested for consistency and

correctness by simulation on matlab and then implemented on the actual system. All

the matlab codes and c codes have been attached as appendix and results have been

included in the report. To increase the DF accuracy, method of interpolation has been

utilized and the same has been tested by developing an algorithm and implementing it

on matlab. Even the range calculation and localization of the source algorithm has been

developed and implemented on matlab and codes attached with the report for future

developments.

7.2 Improvements and future work

The complete DF system for frequency range 2.4-2.5 GHz has been

discussed in previous chapter. This system is just a prototype hence there is a large

52

scope of improvements and future work required for developing an indigenous DF

system which can be practically employed and used in real operational environment.

This DF system has been developed in a modular fashion and also

algorithm like range calculation, multiple signal classification, interpolation, etc are

developed on matlab so that this all can form a base for development of fully integrated

DF system. Continuing with the work done in this project the following things can be

implemented in future.

1. The first thing which has to be changed in the system is to increase

the frequency range of the system. This will require a rugged and broadband

antenna system. We may divide the required band into sub part and use

different antenna array for each band.

2. Current work was focused on implementing the correlative

interferometry algorithm for a fixed signal source. The new system can be

developed for multiple signals as shown in the MUSIC algorithm.

3. The system which was developed during the project was modular

but in the new system power divider, phase detector, amplifier, etc can be

developed on a single PCB which will provide strength to the system.

4. Number of antenna elements in a circular can be increased based

on the DF accuracy required.

5. Monitoring section can be included with the DF system if needed.

6. DSP board can be utilized instead of microcontroller card.

7. A front end interface can be developed for DF system and the DF

board can be integrated with computer so that proper planning for DF task

can be done based on requirements, also the data of signal intelligence can

be stored for future reference.

53

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5. David Adamy, “EW 101 A First Course in Electronic Warfare” Artech House

Boston London.

6. Joseph J Carr, “Practical Antenna Handbook”, Fourth Edition TAB Electronic

McGraw Hill Publication.

7. Doppler System Inc. “Web Note on Theory of Operation”, Series 5900

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8. Rode-Schwarz, Chapter 1, “Introduction to Theory of direction finding”

www.rohde-schwarz.com/www/downcent.nsf/file/chapter1_introduction.pdf

9. Rode-Schwarz, Chapter 3, “Classical direction finding methods” www.rohde-

schwarz.com/www/downcent.nsf/file/chapter3

10. Cheol-Sun Park, Dae Young Kim, “The Fast Correlative Interferometer DF

Using I/Q Demodulator”, Asia-Pacific Conference on Communication, Aug 2006.

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54

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