Signal characterisation and processing in the forward scatter mode of bistatic passive coherent location systems
© Gashinova et al.; licensee Springer. 2013
Received: 30 July 2012
Accepted: 5 February 2013
Published: 27 February 2013
The transfer of the forward scatter (FS) concept to passive coherent location (FS PCL) systems provides a new emerging area of research. This article is dedicated to the investigation of various aspects of a bistatic passive coherent location (PCL) system operating in the FS mode. For efficient signal processing, appropriate FS PCL system analysis is presented. It is shown that using a relatively small modernisation of traditional signal processing algorithms, a PCL system may effectively operate against stealth and low profile targets crossing or being located in the vicinity of the radar baseline. The FS signals have been analysed in view of finding key effects and parameters influencing the waveforms and spectra which define the overall signal processing. Experimental results are given to validate the presented analysis.
Bistatic radars (BRs) have experienced resurgence in the radar community over the last decade, [1, 2] and the concept of passive coherent location (PCL) plays an important role in this new wave of interest.
Example emitters of opportunity for PCL systems
Functionality as PCL
Medium to long range air target detection and tracking.
Digital Audio Broadcasting (DAB) 
LEO satellite communication 
Mobile Cellular Radio (MCR) 
Short to medium range air targets and local vicinity surface target observations.
Indoor and close range security applications intended for human and vehicle detection.
Hybridisation with SAR imaging.
Synthetic Aperture Radar (SAR) 
Satellite TV (SatTV) 
There are both advantages and shortcomings of forward scatter radar (FSR). However, commonly shared opinion is that FSR has rather limiting capabilities, such as limited coverage due to narrow angular width of the main shadow lobe, strong clutter, presence of the Doppler dead zone, and, therefore, will not significantly contribute into the performance of PCL. In [17–23], however, it was shown that dedicated FSR can provide excellent Doppler resolution and its algorithms enable both estimation of target trajectory and speed and classification. This article aims to show that FSR when integrated into PCL systems will have the same capabilities as in the case of dedicated FSR, will add extra benefits to the existing bistatic mode of operation of PCL and can practically be implemented on both hardware and software levels without requiring significant restructuring.
FSR forms a sub-class/mode of BR, one where targets are observed at large bistatic angles β ≈ 140°–180°. FSR signatures are formed in a specific way, which govern the signal processing algorithms used. Depending on the scenario, signatures are composed of varying contributions of both FS shadowing of the direct path signal and bistatic scattering when the target is in the vicinity of the baseline [19, 24, 25]—to note, in PCL systems the direct path is usually referred to as the transmitter–receiver leakage signal [15, 16] and in bistatic configuration is typically unwanted. This highlights an advantage of FSR: the ability to detect stealth targets through observing perturbations in the direct path signal. As another example, the FS effect significantly increases target radar cross section (RCS) in the forward direction, this is irrelevant to target shape and material at least within the optical, or Mie scattering regions. This increase however exists only over a narrow spatial region (the forward scatter main lobe—FSML), thus limiting the use of FSR to ‘microwave fence’ applications. However, using transmitters of opportunity a ubiquitous FSR network could be built thus widening the area of its applicability. It should be mentioned that performance of FSR mode does not depend on the particular PCL signal modulation scheme and, therefore will not influence FSR signal processing complexity, implying that any available transmitter of opportunity could be used for forward scatter concept to passive coherent location (FS PCL) systems.
With this in mind, the main aim of this articleis to explore the integration of an FSR channel/mode into the traditional PCL system to compliment the conventional BR approach. The layout of the article is as follows: Section 2 will present the general passive radar layout, highlighting the inclusion/integration of the FSR channel. Section 3 looks at aspects of target cross section in relation to scattering region and comparison of monostatic and bistatic RCS (MRCS, BRCS) to that of the forward scatter cross section (FSCS). Section 4 concentrates on range resolution and Doppler analysis, indicating the inherent low Doppler frequencies that are observed and can in fact be measured in FSR. Optimal signal processing is also discussed in this section. Section 5 introduces the practical realisation of the system, through discussion of power budget, noise and the concept of the self-mixing receiver. Section 6 provides conclusions, where appropriate, simulations and experimental results from our dedicated FSR studies are included.
2. PCL system topology and overview
In PCL, we assume that a transmitted signal always reaches the designated receiver and therefore Tx and Rx antennas could be viewed as omni-directional with clear line of sight; for VHF and UHF bands’ antennas are physically nearly omni-directional in any case. The remaining variables in Figure 1 will be explained as required in the following sections.
3. Target RCS
An important benefit of using BR in an FS configuration is the enhancement in cross section, both in terms of magnitude and stability. In the following, there is a discussion of RCS in various scattering regimes, supported using the analytically known solution for the sphere. Consequently, EM simulations are provided for typical difficult targets to confirm in an exact way, the benefits of FSCS over BRCS in the appropriate scattering regimes.
3.1. Phenomenology of FSCS
Though derived for a sphere, this equation reflects the general relationship between cross section and the width of the main lobe for targets of any shape, i.e. the FSCS is inversely proportional to the square of the FSML width. We can therefore see (Figure 2) that the ‘penalty’ for the increase in target reflectivity is the narrowing of the FS region, e.g. for the sphere, a 10 dB increase in FSCS in the upper Mie region corresponds to a 40° FSML width reduction.
For comparison and analysis of more complex shapes to emphasise the conclusions drawn above, we must use 3-D full-wave simulation methods.
3.2 Simulation of 3-D BRCS
Simulated BRCS and FSCS for a selection of targets in various scattering regimes
BR (β = 900)/ FSR (β = 1800)
Targets, L (m), H (m), V ( m/s)
L = 0.5, H = 1.8, V = 1.0
Vehicle, LR Discovery
L = 4.8, H = 2.2 , V = 10
L = 2.3, H = 1, V = 5
L = 3.6, H = 0.5, V = 200
L = 8.4, H = 2, V = 50
4. Range Resolution and Doppler in FSR
Two perceived drawbacks of FSR are the loss of range resolution and the Doppler ‘dead zone’. However, even though range resolution may be lost, the excellent Doppler resolution may partly compensate for this. It is also shown that in FSR the very low Doppler frequencies corresponding to the ‘dead zone’ (narrow FS lobe) can be measured and target Doppler signature can be used for detection.
4.1 Range resolution
In the bistatic configuration of Figure 6a, Tg3 is spatially separated due to the receive antenna pattern. In the FS configuration (Figure 6b), Tg3 is spatially separated from the receiver even in the case of a wide beam receive antenna due to the narrow FSML. Range resolution in BR is specified along the bistatic bisector angle. If two targets—Tg1 and Tg2 in Figure 6a—are placed along this bisector (ψ = 0), the range resolution depends on the signal bandwidth Δf 0 and the bistatic angle β. If the second target is shifted relevant to the bisector (Figure 6a, Tg3), it experiences a resolution reduction factor of cosψ. If ψ = 90°, the two targets are on the same iso-range contour and are not distinguishable in the time domain. In BR, the range and angular resolution are coupled, potentially two targets at the same iso-range contour could be resolved if their receive antenna is directional. Assuming that the receive antenna beam width is φ BR, the linear resolution of the two targets on the same iso-range contour could be estimated as ΔR ≈ R R φ BR [rad], where R R is previously defined in Figure 1 as the target to receiver range. Equation (5) shows that under other equal conditions, the range resolution in BR is worse in comparison to MR.
As β → 180° range resolution is dramatically reduced by a factor of cos(β/2) and in the vicinity of the baseline, the range resolution direction is normal to the baseline. Evidently in contrast to BR, targets separated by the angle φ → 90° (Figure 6b, Tg1 and Tg2) are not resolved by means of time or angular resolution. When targets are aligned along the bistatic bisector (Figure 6b, Tg1 and Tg3), any practical resolution could be observed only in ultra-wideband (UWB) FSR , where extremely wide signal bandwidth Δf 0 ‘compensates’ the resolution reduction due to the very low value of cos (β/2).
Or, the angular resolution of two targets form the receiver position will be given by, Δθ FS = θ FS/2 = λ/2h.
4.2 Frequency resolution
Whilst the absence of range resolution is an apparent drawback of FSR, it does however give rise to a non-fluctuating target signal, even for highly manoeuvrable targets. As a result, the maximum coherent analysis time in FSR may be equal to the target visibility time T V . Thus, an absence of range resolution is partly compensated by the excellent frequency resolution.
Maximum coherent integration times for monostatic and FS radar
Δϕ / Δt (°/s) →
Baseline = 40 km
v tg = 50 m/s
λ (m) ↓
For comparison with the monostatic case, Δτ FS and the FSR frequency resolution Δf FS = 1/Δτ FS are shown in the last two columns of Table 3 for the UAV midpoint crossing of a 40-km baseline with speed v tg = 50 m/s. For instance, for a 0.75-m wavelength, the maximum coherent integration time increases from 0.16 in MR (aspect angle rate 0.4°/s) to 19 s in FSR. So, in FSR in addition to a significant increase of RCS in the FS region, the potential time for coherent integration is also much larger than in MR due to the absence of phase fluctuations.
The very high-frequency resolution of FSR enables development of efficient automatic target classification algorithms based on inverse shadow aperture synthesis and this even allows target profile reconstruction [21, 34]. Using the example outlined above we can see that frequency resolution at 0.75-m wavelength with 0.4°/s aspect angle rate in Table 3 is 0.05 Hz for FSR but ~6 Hz for MR.
4.3 FS Doppler signature
Thus, the Doppler shift observed within the FSML is small and for most practical cases is in the order of a few Hz. In the case of traditional BR and PCL systems, this area of low Doppler would be referred to as a dead zone and excluded from the analysis—special techniques should be applied to detect these signals, as will be discussed. Such a low Doppler frequency spectrum of the main energy part of the signal requires an analysis of the radar sensitivity and, in particular, the effect of the phase noise of the transmitter on FSR performance.
5. Practical Realisation of FSR
Here we look at the actual system design though consideration of power budget, phase noise and ultimately the hardware required in order to realise the system physically and that allows it to function in the manner shown in previous sections.
5.1 Power budget and phase noise
In FSR, the signal scattered from a target is received as a modulation on top of the direct path (leakage) signal and is consequently subject to leakage signal phase noise. Lets first evaluate the target signal-to-leakage ratio (SLR) in FSR.
where h T and h R are the transmit and receive antenna elevations, respectively, and h Tg is either the air target altitude or effective height of the surface target, which in the first approximation may be considered as the half of the target height [17, 23].
4.2 Self mixing receiver for PCL FS operational mode
As long as the leakage signal is above the thermal noise of the radar receiver, any nonlinear component could be used as the mixer. Two approaches may be recommended: firstly, an envelope detector with quadrature nonlinear characteristic and secondly, the received signal strength indicator output of amplifiers contained in off-the-shelf chipsets.
It removes the phase noise and modulation of the transmitter in FS PCL which makes signals detectable even at nearly zero Doppler shifts.
In addition, removing the transmitter modulation leads to the simple and universal signal processing algorithms for all FS PCL systems, irrelevant of the transmitted waveforms.
PCL has been discussed previously in BR configuration. The transfer of forward scatter concept to PCL systems (FS PCL) provides a new emerging area of research. PCL can naturally use its network structure of transmitters of opportunity, e.g. TV and DAB broadcasting and cellular radio networks, various GNSS systems, which makes FS PCL even more attractive in comparison with a single or chained dedicated FSR.
In this article, we have analysed the performance of the FSR in relation to PCL on its ability to deliver information on ‘difficult’ targets, have shown its advantages such as enhanced cross section in forward direction, Doppler resolution and utilising the leakage signal as a pseudo local oscillator to mix with the received target FS signal to produce the Doppler output. We also have scrutinised the FS signals in view of finding key effects and parameters influencing the waveforms and spectra which define the overall signal processing.
The region in the vicinity of the baseline has been considered in many cases as a ‘dead zone’ due to the very low Doppler frequency of the moving target in this region. Utilising a relatively simple modification in signal processing at hard and/or software levels, this region can be considered as operational region for FS PCL with enhanced target detection and automatic target recognition capabilities. Also it is worthwhile noting that due to self-mixing receiver architecture in FS mode the modulation of the specific PCL transmitter of opportunity does not influence the processing of the signals. Consequently, an FS PCL network can be formed using a multitude of signals from various transmitters of opportunity.
The PCL operating in VHF/UHF bands can particularly be recommended for airborne target detection in the FS region, while for the surface targets practically all PCL sources could be used.
- Willis NJ, Griffiths HD: Advances in Bistatic Radar. Raleigh, NC: SciTech Publishing; 2007.View ArticleGoogle Scholar
- Cherniakov M (Ed): Bistatic Radar: principles and practice. : John Wiley & Sons; 2007.Google Scholar
- Kuschel H, O’Hagan D: Passive radar from history to future. Vilnius, Lithuania: in 11th International Radar Symposium (IRS) 2010; 2010:1-4. 16–18 JuneGoogle Scholar
- Howland PE, Maksimuk D, Reitsma G: FM radio based bistatic radar. IEE Proceedings - Radar, Sonar and Navigation 2005, 152(3):107-115. 10.1049/ip-rsn:20045077View ArticleGoogle Scholar
- Poullin D, Flecheux M: Recent progress in Passive Coherent Location (PCL) concepts and technique in France using DAB or FM broadcasters. In Proc. of IEEE Radar Conference RADAR’08, Rome, Italy. : ; 2008:1-5.Google Scholar
- Saini R, Cherniakov M: DTV signal ambiguity function analysis for radar application. IEE Proceedings - Radar, Sonar and Navigation 2005, 152(3):133-142. 10.1049/ip-rsn:20045067View ArticleGoogle Scholar
- Cherniakov M, Nezlin D, Kubik K: Air target detection via bistatic radar based on LEOs communication signals. IEE Proceedings - Radar, Sonar and Navigation 2002, 149(1):33-38. 10.1049/ip-rsn:20020129View ArticleGoogle Scholar
- Tan DKP, Sun H, Lu Y, Lesturgie M, Chan HL: Passive radar using Global System for Mobile communication signal: theory, implementation and measurements. IEE Proceedings - Radar, Sonar and Navigation 2005, 152(3):116-123. 10.1049/ip-rsn:20055038View ArticleGoogle Scholar
- Colone F, Woodbridge K, Guo H, Mason D, Baker CJ: Ambiguity Function Analysis of Wireless LAN Transmissions for Passive Radar. IEEE Trans. Aerosp. Electron. Syst. 2011, 47(1):240-264.View ArticleGoogle Scholar
- Guo H, Woodbridge K, Baker CJ: Evaluation of WiFi beacon transmissions for wireless based passive radar. In Proc. of IEEE Radar Conference RADAR’08, Rome, Italy. : ; 2008:1-6.Google Scholar
- Saini R, Rui Z, Cherniakov M: Development of space-surface bistatic synthetic aperture radar with GNSS transmitter of opportunity. In Proc. of IEEE Radar Conference RADAR’08, Rome, Italy. : ; 2008:1-6.Google Scholar
- Cherniakov M, Saini R, Zuo R, Antoniou M: Space surface bistatic SAR with space-borne non-cooperative transmitters. In European Rad. Conf. EURAD2005, Paris, France. : ; 2005:9-12.Google Scholar
- Walterscheid I, Espeter T, Brenner AR, Klare J, Ender JHG, Nies H, Wang R, Loffeld O: Bistatic SAR Experiments With PAMIR and TerraSAR-X—Setup, Processing, and Image Results. IEEE Trans Geosci Rem Sens 2010, 48(8):3268-3279.View ArticleGoogle Scholar
- Cazzani L, Colesanti C, Leva D, Nesti G, Prati C, Rocca F, Tarchi D, Ground-Based A: Parasitic SAR Experiment. IEEE Trans Geosci Rem Sens 2000, 38(5):2132-2141. 10.1109/36.868872View ArticleGoogle Scholar
- Griffiths HD, Baker CJ: Passive coherent location radar systems. Part 1: performance prediction. IET Radar, Sonar & Navigation 2005, 152(3):153-159. 10.1049/ip-rsn:20045082View ArticleGoogle Scholar
- Baker CJ, Griffiths HD, Papoutsis I: Passive coherent location radar systems. Part 2: waveform properties. IET Radar, Sonar & Navigation 2005, 152(3):160-168. 10.1049/ip-rsn:20045083View ArticleGoogle Scholar
- Sizov V, Cherniakov M, Antoniou M: Forward Scattering Radar Power Budget Analysis for Ground Targets. IET Radar, Sonar & Navigation 2007, 1(6):437-446. 10.1049/iet-rsn:20060174View ArticleGoogle Scholar
- Cherniakov M, Abdullah RSAR, Jancovic P, Salous M, Chapursky V: Automatic ground target classification using forward scattering radar. IEE Proceedings on Radar, Sonar and Navigation 2006, 153(5):427-437. 10.1049/ip-rsn:20050028View ArticleGoogle Scholar
- Gashinova M, Daniel L, Kabakchiev K, Sizov V, Hoare E, Cherniakov M: Phenomenology of signals in FSR for surface targets detection. In International Conference on Radar Systems RADAR 2012. Glasgow, UK: ; 2012:6.Google Scholar
- Cherniakov M, Gashinova M, Cheng H, Antoniou M, Sizov V, Daniel LY: Ultra wideband forward scattering radar: Concept and prospective. In 2007 IET International Conference on Radar Systems, Edinburgh, UK. : ; 2007:1-5.Google Scholar
- Chapurskiy VV, Sablin VN: SISAR: Shadow Inverse synthetic aperture radiolocation. In Proc. of the IEEE-Radar 2000 International Conference, . Alexandria, VA, USA: ; 2000:322-328.Google Scholar
- Cheng H, Sizov V, Antoniou M, Gashinova M, Cherniakov M: Optimal Signal Processing in Ground-Based Forward Scatter Micro Radars. IEEE Trans. Aerosp. Electron. Syst. 2012, 48(4):3006-3026.View ArticleGoogle Scholar
- Kabakchiev K, Daniel LY, Sizov V, Hoare E, Gashinova M, Cherniakov M: Received signal characterization in forward scatter radar for maritime application. In Proceedings of International Radar Symposium 2011 (IRS). Leipzig, Germany: ; 2011:67-72.Google Scholar
- Ufimtsev P: New Insight into the Classical Macdonald Physical Optics Approximation. IEEE Antenn Propag Mag 2008, 50(3):11-20.View ArticleGoogle Scholar
- Ufimtsev PY: Fundamentals of the Physical theory of Diffraction. : John Wiley and Sons; 2007.View ArticleGoogle Scholar
- Howland PE, Griffiths HD, Baker CJ: Passive bistatic radar systems. In Bistatic Radar: Emerging Technology. Edited by: Cherniakov M. : John Wiley & Sons; 2008:394.Google Scholar
- Willis N: Bistatic Radar. : SciTech Publishing; 2007.Google Scholar
- Daniel L, Gashinova M, Cherniakov M: Maritime Target Cross Section Estimation for an UWB FSR Network. In Proc. EuRAD 2008. Amsterdam, Netherlands: ; 2008:316-320.Google Scholar
- Glaser J: Forward Scatter Radar for Future Systems. The WSTIAC Quarterly 2011, 10(3):3-8.Google Scholar
- Skolnik MI: Radar Handbook. 2nd edition. : McGraw Hill; 1989.Google Scholar
- Glaser JI: Bistatic RCS of Complex Objects Near Forward Scatter. IEEE Trans Aero Electron Syst 1985, AES-21(1):70-78.View ArticleGoogle Scholar
- Lee SW, Mittra R: Fourier transform of a polygonal shape function and its application in electromagnetics. IEEE Trans Antenn Propag 1983, 31(1):99-103. 10.1109/TAP.1983.1142981View ArticleGoogle Scholar
- Nathanson FE, Reilly JP, Cohen MN: Radar Design Principles. : McGraw-Hill; 1991.Google Scholar
- Myakinkov A, Kuzin A, Gashinova M, Sizov V, Cherniakov M: Inverse Forward Scatter SAR. In Proc. of the Institute of acoustics, Int. Conf. on Synthetic Aperture Sonar and Synthetic Aperture Radar 2010. Lerici, Italy: ; 2010:152-156.Google Scholar
- Hoeg W, Lauterbach T (Eds): Digital Audio Broadcasting: Principles and Applications of DAB, DAB+ and DMB. : Wiley-Blackwell; 2009.Google Scholar
- QuickSyn Datasheet: Microwave frequency synthesizer. : Phase Matrix. Inc; accessed July 2012, http://www.phasematrix.com/Spec_Sheets/DS_FSW-0010_0020.pdf
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.