Polarimetric Radar Signal Processing
2: Private Consultant, Italy
Polarimetric Radar Signal Processing provides an overview of advanced techniques and technologies developed for polarimetric radars to meet challenging performance requirements. It aims to cover some of the most challenging application fields, including: target detection for active and passive surveillance systems, interference suppression, detection of temporal changes in a given scene, environment classification, automatic target recognition, non-cooperative target imaging, polarimetric coding in radar and SAR systems, pol-SAR ambiguities suppression, space-debris detection, tracking, and classification, estimation of biological and behavioural parameters of insects, precipitations localization as well as type and motion parameters estimation via real-life practical polarimetric weather radar.
The book balances a practical point of view with a rigorous mathematical approach corroborated with a wealth of numerical case studies and real experiments. Additionally, the book has a cross-disciplinary approach as it aims to exploit cross-fertilization by the recent and latest research and discoveries in statistical signal processing theory and electromagnetism.
Each chapter is self-contained and is written by renowned researchers in polarimetric radar signal processing. The emphasis of the book is on both theoretical results and practical applications that clearly show the potential benefits in radar performance using polarimetric diversity in different application domains. Cross referencing and a common notation have been realized so that the related material as well as equations can be easily connected. This significantly enhances the book's value as a reference.
This book is addressed to systems engineers and their managers in civilian as well as defence companies; technical staff in procurement agencies and their technical advisers; students at MSc and PhD levels in signal processing, electrical engineering, systems and defence engineering; and any persons interested in applications of polarimetry theory to radar engineering.
Inspec keywords: radar detection; radar polarimetry; remote sensing by radar; Doppler radar; meteorological radar; atmospheric techniques; radar imaging; synthetic aperture radar
Other keywords: synthetic aperture radar; meteorological radar; radar imaging; radar polarimetry; radar detection; atmospheric techniques; remote sensing by radar; object detection; Doppler radar
Subjects: Optical, image and video signal processing; Lower atmosphere; Physics literature and publications; General electrical engineering topics; Signal detection; Atmospheric, ionospheric and magnetospheric techniques and equipment; Instrumentation and techniques for geophysical, hydrospheric and lower atmosphere research; Radar equipment, systems and applications
- Book DOI: 10.1049/SBRA549E
- Chapter DOI: 10.1049/SBRA549E
- ISBN: 9781839534027
- e-ISBN: 9781839534034
- Page count: 525
- Format: PDF
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Front Matter
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1 Adaptive target detection with polarimetric radars
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Polarization diversity is a key tool to sensibly boost the detection performance of a radar system, especially when the Doppler discrimination is not entirely possible. This is the case of Doppler ambiguous, slowly moving, or tangentially moving targets, which are masked by the clutter environment in conventional pulse-Doppler radars. In these challenging situations, where angle and Doppler features of the radar returns do not allow to distinguish targets from background clutter, multi polarimetric measurements provide valuable information for target detection.
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2 Exploiting polarimetric diversity in passive radar
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Radar polarimetry has been widely used in radar systems aiming at the detection, discrimination, and recognition of targets of interest among other interfering sources. It becomes an essential tool in challenging radar scenarios where the achievable performance is not under control of the radar designer. This is certainly the case of passive radar whose performance largely varies with the radiative properties of the transmitter of opportunity as well as with the severity of the electromagnetic (EM) scenario that typically includes many interfering sources.
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3 Mainlobe jamming suppression for polarimetric multi-channel radar
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In this chapter, assuming that the target and self-defence mainlobe jamming share different polarization characteristics; the ICA-based approach for polarimetric multi-channel radar is developed to suppress mainlobe jamming. Specifically, the signal models of polarimetric multi-channel radar accounting for the target and jamming signals were derived. Then, the P-ICA method was utilized to separate the target component and jamming component while achieving the mainlobe jamming suppression. Finally, numerical simulation results have demonstrated that the P-ICA method can suppress many different signal kinds of jammings, such as the NFM jamming, the NAM jamming and the SMSP jamming, and the types of both the SDJ and ESJ. In addition, it can well overcome the disadvantages of the existing methods in [17, 26] which cannot reject NAM jamming and SDJ jamming, respectively.
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4 Coherent change detection in multi-polarization synthetic aperture radar images
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This chapter has addressed the problem of the multi-polarization SAR coherent CD in the presence of homogeneous unstructured returns, homogeneous structured observations, and partially homogeneous data. For the mentioned environments, to identify the possible temporal changes between the reference and test images, the detection problem has been formulated as a specific binary hypothesis test involving the comparison of the polarimetric covariance matrices associated with the reference and test data. For the homogeneous environment, some CFAR decision rules designed by the means of the theory of invariance in hypothesis testing have been discussed. Subsequently, to improve the detection performance in the presence of homogeneous structured data, a special structure for the polarimetric covariance matrices in the hypothesis testing problem has been accounted for. Finally, the capability to account for a possible scale mismatch factor between the reference and test data has been addressed and some scale invariant decision rules have been discussed.
The performance of the considered strategies has been assessed using measured PolSAR data which revealed the capability of the considered decision rules to correctly identify the temporal changes as well as to provide a good CFAR behaviour even in the presence of power mismatches among the different acquisitions.
Possible future research tracks might consider the extension of the framework relaxing the Gaussian requirement for the data as well as the analysis on other datasets acquired under different environmental and operating conditions.
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5 Classification of covariance symmetries in full-polarimetric SAR images
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This chapter has dealt with the problem of covariance matrix classification in PolSAR images on the base of the special structures assumed under symmetrical properties of the returns associated to the pixels under test. In particular, the chapter has focused on both homogeneous and heterogeneous SAR images' classification, including a description of the symmetry classification within the PolInSAR imagery. For all the described frameworks, the problem has been formulated as a multiple hypothesis test comprising both nested and non-nested hypotheses. For this reason, it has been solved by resorting to the well-known MOS rules to overcome the limitations of the classic GML approach.
Results conducted on both simulated and L-band real-recorded PolSAR data have proven the effectiveness of the described methodologies, thus paving the way for further applications, e.g., as a preliminary step of a more sophisticated two-stage algorithm aimed at, for instance, classifying the scene.
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6 Polarimetric information to enhance synthetic aperture radar automatic target recognition capabilities
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This chapter has investigated the potential benefits of the use of polarimetry when dealing with ATR. CTD is particularly suitable to represent man-made targets and is physically interpretable. Moreover, it was shown how a particular decomposition belonging to this family of polarimetric decompositions can improve the performance of ATR frameworks. In particular, it was shown how the roll-invariant Krogager decomposition could be easy and effective to integrate in a feature-based ATR framework exploiting invariant image moments. The results presented demonstrate that the use of polarimetric information helps to enhance target-recognition capabilities as well as reduce data collection requirements for classifier training purposes.
However, a number of research questions still exist in this area, such as the selection of the best polarimetric decomposition for ATR purposes, or the possibility to design a custom ATR-oriented polarimetric decomposition with the aim to extract the most relevant information for the target-recognition task. Another topic to investigate is the necessity to differentiate approaches based on the level of target classification required. For example, it could be useful to assess which type of approach/decomposition would be more suited for different classification levels. As often only two polarimetric channels are available, it would be interesting to understand how much of the polarimetric information that supports the ATR task can still be extracted. A different perspective would be to investigate the latest advances in artificial intelligence with CNNs applied to the ATR task, and in this sense, recently some progress has been made [40, 41]. However, these techniques have not reached a sufficient level of maturity in the field and more research effort would be required in the future. The above are likely to be explored in the future by the research community, broadening the interest on this relevant application domain and strengthening the use case for polarimetric SAR sensors.
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7 Polarimetric inverse synthetic aperture radar
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Pol-ISAR has proven to be more accurate and more effective than single-channel ISAR when used for target recognition. Given the limited amount of such systems and available data and literature, this is a field that can still benefit from additional study and experimentation to fully exploit its potential. The use of polarimetry involves additional receiving channels in the radar system and therefore it increases the complexity of cost of the overall radar system. This creates a trade-off that must be considered when designing ISAR systems for target recognition. Nevertheless, when size, weight, power and cost constraints are favourable, the benefit of using full polarization is significant both in terms of image quality, by producing better focused images, and in terms of the amount of information (features) that can be exploited to improve target classification performances.
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8 UWB short-range polarimetric imaging and its potential for target classification
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Ultra-wideband (UWB) short-range polarimetric imaging provides not only high spatial resolution but also polarimetric scattering features of targets, which has great application potentials in subsurface survey with ground penetrating radar, through-the-wall imaging, security check, and so on. In this chapter, two key aspects of the UWB short-range polarimetric imaging, i.e., full-polarimetric data acquisition and polarimetric image reconstruction, are discussed [1, 2].
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9 Robust transceiver design for polarimetric radars
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Polarization, together with the amplitude, time, frequency, phase, and bearing descriptors of radar signals, completes the information that can be obtained on target returns in modern radars [1]. Radar polarization exploits the vector nature of electromagnetic fields and has become an indispensable tool in radar systems. Since its birth in the 1950s, polarimetric radar has played an important role in military and civilian areas including air defense, remote sensing, weather surveillance, etc. [2-5]. Not surprisingly, in the last decades, the exploitation of information on the echo polarization state to improve radar performance has represented a research topic of remarkable interest [6-15].
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10 An ambiguity suppression scheme for quad-pol SAR based on quasi-orthogonal waveforms
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Radar waveform design has received considerable attention along the years [1-3] and represents a key factor to boost radar performance. Quasi-orthogonal waveforms represent a promising methodology to suppress the unwanted ambiguity energy in synthetic aperture radar (SAR) systems [4, 5]. However, unlike communication systems, the orthogonality constraint for SAR demands more challenges, due to the need of achieving desired imaging performance in the presence of a distributed target scene. The cross-correlation energy (CCE) between the transmitted pulses, resulting from range-focusing process, introduces artifacts at different unambiguous range-azimuth positions, which can be either smeared or concentrated [6, 7]. Therefore, to mitigate the effects of ambiguities, quasi-orthogonal waveforms with a low CCE delineate a convenient option. However, according to the Parseval's theorem, Krieger [8] pointed out that waveforms with flat spectra (e.g. up-down chirp waveforms) present a fixed CCE value regardless of the specific pair, thus cueing the adoption of non-flat spectra to grant CCE reduction. Last but not least, SAR is an imaging sensor which calls for the transmitted waveforms to exhibit low peak to side lobe ratios (PSLRs) and integrated side lobe ratios (ISLRs) in order to ensure satisfactory imaging performance.
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11 Fully polarimetric monopulse spaceborne radar for space situational awareness
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This chapter has outlined a novel SBR payload functional architecture for SSA as a fully polarimetric monopulse-based single input multiple output (SIMO) radar in the Ka band taking into account space-qualified technologies in both digital and RF domains. The envisaged architecture in Figure 11.3 acquires a complex data hypercube and comprises a filter bank with a group of Doppler frequency offsets not for estimating a target radial velocity (due to the inherent ambiguity of the echo range-rate in cueing the debris range-rate) but rather as a means to enforce Doppler tolerance on the PC scheme and avoid straddle losses. The adaptivity of such a radar architecture allows including robust and selective debris detection schemes tailored to CFAR-like paradigms. Finally, specific parameter estimates from a burst of pulse echoes make provision for further Bayesian inference capabilities on small-size debris dynamic states as well as RCS-related signatures via time series analysis. For this latter purpose, the acquisition of echoes related to the motion of a debris for an elapse time up to several hundreds of milliseconds could be operatively extended to a few seconds, thus augmenting the time on target with additional measurement and gauging perspectives. By selecting an optimal transceiver configuration such that the SBR AESA transmit beam points the debris target minimizing a cost function (e.g. as per a joint waveform and beam control optimisation with ties to [83]), it would be possible to refine radiometric signatures insights. In particular, this would entail performing a time series analysis on RCS signatures embedding polarimetric scattering descriptors [84] and exploiting an adaptive polarization design for tracking (see also section 16.4 in [85]). Last but not least, it is worth stressing that the SIMO SBR concept discussed in this chapter has been tailored to a PWS contact collection strategy. Interestingly, Reference 86 extends the complexity of the SBR payload with a Code Division Multiplexing Multiple Input Multiple Output (MIMO) configuration entailing a Track While Simultaneous Search contacts collection strategy.
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12 Polarization information processing in insect radar
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Migratory insects are usually small in size, and many of them fly at night at high altitude. Traditional methods for monitoring migratory insects include optical observation, ovarian dissection, net trapping, and light trapping. Although these methods provide a preliminary understanding of the migration mechanism of migratory insects, they are time-consuming and laborious and can only monitor limited range. More importantly, such methods may interfere with the flight of insects and make the interpretation of observations more difficult.
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13 Polarimetric weather radar signal processing
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The weather radar database of the World Meteorological Organization (WMO) provides more than 1 000 entries by the end of 2020. Almost all radars are operating in S-, C-, or X-band, and more than 340 are polarimetric. Examples are shown in Figure 13.1 and Figure 13.2. Considering that the real numbers are larger because the database is not complete and not up-to-date, the number of ground-based weather radar installations probably exceeds the number of all other types of large-scale, civil-used ground-based radars, including primary radars.
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14 Meteorological polarimetric phased array radar
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Polarimetric meteorological radars have become crucial for the detection and short-term forecast of hazardous weather, as well as quantitative precipitation estimation (QPE). The ability to directly identify hail and gauge its size, detect tornado debris, and anticipate flash floods sets these radars apart from the classical single-polarized ones. Weather agencies in many countries have deployed and/or upgraded their radar systems to dual polarization, including the US National Weather Service (NWS) which completed the upgrade of its Weather Service Radar-1988 Doppler (WSR-88D) network in 2013. Recent experience with the WSR-88D and other operational radars has exceeded expectations, well justifying the upgrade cost, which was about 5% of the initial procurement. The high quality of the quantitative polarimetric measurements has set a standard for any future polarimetric weather radar.
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Back Matter
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