3
PRACTICAL ISSUES FOR RADAR
TRACKING
3.1 TRACK INITIATION AND CLUTTER REJECTION
The problems of clutter rejection and track initiation are very much interwined.
It is possible to use track initiation to help in the rejection of clutter. On the
other hand it is possible to use appropriate clutter rejection techniques to reduce
the track initiation load. Examples of these are discussed in the following
sections.
3.1.1 Use of Track Initiation to Eliminate Clutter
The radar track initiator can be used to eliminate clutter by passing the clutter
returns as well as target returns, which are indistinguishable initially, into the
track initiation filter. However, only those returns that behave like a moving
target would be passed into track at the output of the track initiation filter, thus
finally eliminating the clutter returns. For example, the stationary clutter returns
would be dropped by the track initiation filter (or classified as clutter returns for
association with future such returns).
The use of this approach can in some cases potentially provide about an
order of magnitude or more increase in system sensitivity. This is the case when
dealing with spiky clutter. In order to achieve a low false-alarm probability due
to spiky clutter returns at the input to the track initiation filter, it is necessary
that the detector threshold be increased by 10 dB or more above what would be
required if the clutter were not spiky, that is, if the clutter were Rayleigh
distributed at the output of the receiver envelope detector (which implies that
it has a Gaussian distribution at the input to the envelope detector). This is
shown to be the case in Figure 3.1-1 for spiky sea clutter, rain clutter, lognormal
111
Tracking and Kalman Filtering Made Easy. Eli Brookner
Copyright # 1998 John Wiley & Sons, Inc.
ISBNs: 0-471-18407-1 (Hardback); 0-471-22419-7 (Electronic)
clutter, and Weibull clutter for low probabilities of false alarm of 10

The radar coverage is broken down into small range and bearing regions. For
each of these regions the returns from eight scan are stored. By way of
illustration, Figure 3.1-2 plots an example set of such returns seen as range
versus bearing and time. These are the returns from one of the range–bearing
regions mentioned. It is next determined if any set of these returns correspond
to a target having a constant velocity. Return numbers 1, 4, 6, 10, 12, and 14
form the returns from such a constant-velocity target, the target having a
velocity in the band between 28 and 35 knots. The rule used for declaring a
target present in a Doppler band is that M out of N returns be detected in the
band. Here N ¼ 8 and typically M would be of the order of 5.
The retrospective detector was implemented by APL on the AN/FPS-114
radar mounted on Laguna Peak on the California coast. This S-band radar has a
range resolution of 50 ft and azimuth beamwidth of 0.9

. Its scan period is 4 sec
with no coherent Doppler processing being used. Figure 3.1-3 shows the raw
data observed in the lower southwest quadrant after constant false-alarm rate
(CFAR) processing. The returns from 100 scans are displayed in the figure. The
coverage is out to a range of 9 nmi. A digital range-averaging logarithmic
CFAR was used by the system for the results shown in Figure 3.1-3. The results
shown in Figure 3.1-3 were obtained without the use of the retrospective
detector. A high false-alarm rate, about 10
À3
, was used in obtaining the results
of Figure 3.1-3. This resulted in about 2000 false alarms per scan. In this figure
the sea clutter false alarms are indistinguishable from small target returns
resulting from a single scan. Figure 3.1-4 shows the results obtained after
retrospective detector processing; again 100 scans of data are displayed. The
retrospective detector has reduced the false-alarm rate by at least four orders of
magnitude. The ships and boats in the channel are clearly visible. The reduction

returns from Eight Scans; (c) eight scans of data with trajectory filters applied. (After
Prengaman, et al., ‘‘A Retrospective Detection Algornithm for Extraction of Weak
Targets in Clutter and Interference Environments,’’ IEE 1982 International Radar
Conference, London, 1982.)
Figure 3.1-3 Raw data observed in lower southwest quadrant after CFAR processing
(100 scans of data; 9 nmi total range). (After Prengaman, et al., ‘‘A Retrospective
Detection Algorithm for Extraction of Weak Targets in Clutter and Interference
Environments,’’ IEE 1982 International Radar Conference, London, 1982.)
TRACK INITIATION AND CLUTTER REJECTION
115
3.1.2 Clutter Rejection and Observation-Merging Algorithms for
Reducing Track Initiation Load
In this section we shall describe how clutter rejection and observation-merging
algorithms are used to reduce the track initiation load for a coherent ground
two-dimensional surveillance radar. A two-dimensional radar typically is a
radar that has a vertically oriented narrow fan beam (see Figure 1.1-1) that is
Figure 3.1-4 Results obtained after retrospective detector processing using 100 scans
of data. (After Prengaman, et al., ‘‘A Retrospective Detection Algorithm for Extraction
of Weak Targets in Clutter and Interference Environments,’’ IEE 1982 International
Radar Conference, London, 1982.)
Figure 3.1-5 Retrospective detector output after 1000 scans of data (about 1 hr of
data). (After Prengaman, et al., ‘‘A Retrospective Detection Algorithm for Extraction of
Weak Targets in Clutter and Interference Environments,’’ IEE 1982 International Radar
Conference, London, 1982.)
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PRACTICAL ISSUES FOR RADAR TRACKING
scanned 360

mechanically in azimuth about the local vertical axis [1]. Such a
radar provides two-dimensional information: slant range and the bearing angle

TABLE 3.1-1. Retrospective Detector
Radar demonstrated on:
S-band AN/FPS-114 at Laguna Peak, CA
Resolution: 0.1 msec Â0:9

4-sec scan-to-scan period
1500 ft altitude
Retrospective processor: special purpose, consisting of six 6 Â 6-in. wire wrap cards
containing 250 small and medium integrated circuits; total power: 30 W
(Late–1970s/early–1980s technology.)
Performance results: with single-scan false-alarm rate set at 2000 per scan, after
100 scans false-alarm rate reduced by at least four orders of magnitude, after
1000 scans ($ 1 hr) only a few alarms visible
TRACK INITIATION AND CLUTTER REJECTION
117
from which echoes are expected. For example, if the maximum range for the
radar is 100 nmi, then the pulse-to-pulse period would be (100 nmi)
(12.355 nmi/msec) ¼ 1235 msec or greater. The system PRF would then be
1=1235 msec ¼ 810 Hz. For a 1.3-GHz carrier frequency L-band radar an
approaching target having a Doppler velocity of 182 knots would give rise to a
Doppler-shifted echo having a Doppler shift equal to the PRF of 810 Hz.
Because we have in effect a sampled data system with a sample data rate of
810 Hz, any target having a target velocity producing a Doppler shift higher
than the sampling rate would be ambiguous with a target having a Doppler shift
lower than the sampling rate. For example, a target having a Doppler velocity of
202 knots would appear as a Doppler-shifted signal produced by a target having
a Doppler velocity of 202 knots modulo the sampling rate of 182 knots, or
equivalent 20 knots. Thus we would not know if the target actually was going at
202 knots or 20 knots, hence the ambiguity. The use of the second PRF for the
second set of N pulses removes this ambiguity problem. This is done by the

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PRACTICAL ISSUES FOR RADAR TRACKING
threshold varies with range and azimuth since the clutter strength varies with
range and azimuth. To determine what value the threshold should be set at for a
given range–azimuth cell, a clutter map is generated. For this clutter map the
strength of the clutter for each range–azimuth cell of the radar is stored in
memory. Typically the power of the echo in a particular range–azimuth cell
from the last H scans (where H might be of the order of 7 to 10) are averaged to
generate the clutter strength for this cell. An exponentially decaying average is
typically used for ease of implementation, it then being possible to implement
the filter with a simple feedback infinite-impulse response filter rather than the
more complicated finite-impulse response filter. The above described processor
is the Lincoln Laboratory MTD [41, 42].
Lincoln Laboratory first implemented an MTD for the FAA experimental
AN/FPS-18 air traffic control radar at the National Aviation Facilities
Engineering Center (NAFEC). It was installed in 1975. The FPS-18 is an
S-band (2.7 to 2.9 GHz) radar having a PRF of 1000 to 1200 Hz [41, 42, 44].
For this radar, in effect, N ¼ 8, with eight Doppler filters used to process eight
echo pulses. The coherent processing of a set of N ¼ 8 echoes having a
specified PRF is called a coherent procesing interval (CPI). There are thus eight
Doppler outputs per range cell per CPI. Figure 3.1-6 shows a typical system
Figure 3.1-6 Typical ASR single-scan return from single target. Radar range
resolution was
1
16
nmi while Doppler resolution was about 16 knots. (From Castella,
F. R. and J. T. Miller, Jr., ‘‘Moving Target Detector Data Utilization Study,’’ IEE
Radar—77, London, 1977.)
TRACK INITIATION AND CLUTTER REJECTION
119

of only one range cell response, one Doppler cell response, or one bearing cell
response. In contrast, for aircraft targets for which there is a firm track, only 15
TABLE 3.1-2. Sample Centroid Statistics
Percent of Percent of
Characteristics All Centroids Firm Track Centroids Only
Number of CPIs ¼ 1 78.7 15.2
Maximum number of Doppler cell 78.7 13.7
detections per CPI per range cell ¼ 1
Maximum range extent ¼ 1 79.3 21.0
Total centroids considered 34,445.0 3485.0
Source: After Castella and Miller [44].
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PRACTICAL ISSUES FOR RADAR TRACKING
to 21% of the echoes will consist of only one range cell response, one Doppler
cell response, or one bearing response. Figure 3.1-7 shows how effectively
clutter returns can be eliminated by using an algorithm that requires two or
more bearing returns (that is, CPI returns) for the target to be declared detected.
Figure 3.1-7a shows all the target detections obtained in a 50-sec interval if a
target detection is based on the observation of one CPI return. Figure 3.1-7b
shows the radar target detections if it is required that two or more CPIs be
observed. More than 75% of the original centroids have been eliminated using
this simple algorithm. Yet the number of target tracks is seen to be virtually
identical for both displays.
Figure 3.1-8 shows the benefits accrued from using the following two
constraints for declaring a target detection: (a) detection on two or more CPIs
and (b) detection on two or more Doppler cells per range–bearing cell. Figure
3.1-8a gives the resulting detections of 335 scans when no constraints are used
for declaring a detection; that is, detection is based on observing one or more
range–Doppler CPI detections. For this case 54 tracks were observed. Figure
3.1-8b gives the results when the above two constraints were used. The number

29, 32, 33, 41, 42, 44 to 61, and 135.
The clutter suppression and track initiation algorithms act as filters for
reducing the number of false tracks. Figure 3.1-9 illustrates this for a system
designed by APL [56]. This system applies various algorithms for suppressing
real-world clutter for a two-dimensional shipboard surveillance radar. For this
system there are 6 Â 10
6
samples per scan. These samples are filtered down to
just 392 initial contacts. After further screening these in turn are filtered down
Figure 3.1-7 (a) Target detections obtained in 50-sec interval when target detections
are based on observation of only one CPI return. (b) Target detections when two or more
CPIs are required for declaring its presence. (From Castella, F. R. and J. T. Miller, Jr.,
‘‘Moving Target Detector Data Utilization Study,’’ IEE Radar—77, London, 1977.)
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PRACTICAL ISSUES FOR RADAR TRACKING
to 35 possible track updates and 6 tentative tracks. On the average, for the
system under consideration only 1 out of 15 of the tentative tracks becomes a
firm track after further processing. The 35 possible track updates are filtered
down to just 21 firm track updates.
Feedback can be used at various stages of a well-designed system in order to
reduce the number of false tracks and enhanced the target detectability. The
enhancement of target detectability is achieved by lowering the threshold in
prediction windows where the track updates are expected to appear. This proce-
dure is referred to as ‘‘coached’’ detection; see reference 8.
Feedback for controlling the threshold over large areas of coverage have
been used in order to lower the false-alarm rate per scan [16]. This is called area
Figure 3.1-7 (Continued)
TRACK INITIATION AND CLUTTER REJECTION
123
CFAR control. It was used in the Lincoln Laboratory ATC experinental ASR-7

125
Figure 3.1-9 Joint action of clutter suppression and track initiation as filters for
reducing number of false alarms due to severe clutter and radio frequency interference
(RFI). (From Bath et al., ‘‘False Alarm Control in Automated Radar Surveillance
Systems,’’ IEE 1982 International Radar Conference, Radar—82, London, 1982.)
Figure 3.1-10 Improvement provided by feedback area CFAR processing: (a) radar
display without area CFAR; (b) display with area CFAR. (From Anderson, J. R. and
D. Karp, ‘‘Evaluation of the MTD in a High-Clutter Environment,’’ Proceedings of IEE
International Radar Conference, # 1980 IEEE.)
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PRACTICAL ISSUES FOR RADAR TRACKING