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Passive Radar signifying the localisation of a target by radar measurements without using own controlled emissions has been discussed, tried, reinvented, and matured within the last 80 years. Its advantages, like covert operation and saving the costs of a transmitter, are obvious. Military as well as civilian interests combined with the advances in technological developments have recently boosted research on passive radar and passive radar systems are currently approaching the market. This tutorial shall give an overview of the history, development, and processing in passive radar and enable the interested reader to further investigate the subject exploiting the presented material together with the cited references.

In recent years, passive radar has been investigated for airborne applications in imaging and detection of ground targets. There are challenges with detection of land targets from an airborne platform due to platform motion which causes the clutter Doppler to spread and the presence of discrete scatterers which can be strong and confused with targets of interest. In this paper, the problem of heterogeneity in the ground clutter is addressed through a complementary direct data domain algorithm that exploits knowledge of the ground clutter. Once an estimate of the ground clutter is found, it can be subtracted from the original range Doppler map to reveal potential targets. The performance of this novel multichannel algorithm is assessed using a Monte Carlo simulation with simulated data.

In this work, we focus on passive polarimetric ISAR for ship target imaging using DVB-S signals of opportunity. A first goal of the research is to investigate if, within the challenging passive environment, different scattering mechanisms, belonging to distinct parts of the imaged target, can be separated in the polarimetric domain. Furthermore, a second goal is at verifying if polarimetric diversity could enable the formation of ISAR products with enhanced quality with respect to the single channel case, particularly in terms of better reconstruction of the target shape. To this purpose, a dedicated trial has been conducted along the river Rhine in Germany by means of an experimental DVB-S based system developed at Fraunhofer FHR and considering a ferry as cooperative target. To avoid inaccuracies due to data-driven motion compensation procedures and to fairly interpret the polarimetric results, we processed the data by means of a known-motion back-projection algorithm obtaining ISAR images at each polarimetric channel. Then, different approaches in the polarimetric domain have been introduced. The first one is based on the well-known Pauli Decomposition. The others can be divided in two main groups: (i) techniques aimed at separating the different backscattering mechanisms, and (ii) image domain techniques to fuse the polarimetric information in a single ISAR image with enhanced quality. The different considered techniques have been applied to several data sets with distinct bistatic geometries. The obtained results clearly demonstrate the potentialities of polarimetric diversity that could be fruitfully exploited for classification purposes.

This article addresses the problem of clutter cancelation for slowly moving target detection and localization in multichannel passive radar onboard mobile platforms. A post-Doppler space-time adaptive processing (STAP) approach is exploited in the case of an angle-dependent imbalance affecting the receiving channels. While the clutter suppression capability is ensured by the adaptivity of space-time filtering, different solutions are compared, aimed at recovering the detection performance losses associated with channel calibration errors. A space-time generalized-likelihood ratio test (GLRT) scheme is considered, where the steering vector is not specified in the spatial domain, resulting in a noncoherent integration of target echoes across the receiving channels. This is compared with a fully coherent GLRT scheme where echoes from the stationary scene are exploited for the proper calibration of spatial steering vector mismatch. The first scheme proves to be a simple solution for target detection in the passive radar case, offering comparable clutter cancelation capability. The second scheme, at the expense of an additional stage, offers slightly better detection performance and preserves target direction-of-arrival (DoA) estimation capability. Finally, the STAP scheme is employed for the maximum-likelihood estimation of target DoA, evaluating the role of the steering vector calibration against the negative impact of channel imbalance. The effectiveness of the proposed approaches is tested against both simulated and experimental data from a DVB-T-based mobile passive radar.

This paper deals with the problem of detection and direction of arrival (DOA) estimation of slowly moving targets against clutter in multichannel mobile passive radar. A dual cancelled channel space-time adaptive processing (STAP) scheme is proposed, aiming at reducing the system computational complexity, as well as the amount of required training data, compared to a conventional full array solution. The proposed scheme is shown to yield comparable target detection capability and DOA estimation accuracy with respect to the corresponding full array solution, despite the lower computational cost required. Moreover, it offers increased robustness against adaptivity losses, operating effectively even in the presence of a limited set of training data, as often available in the highly non-homogeneous clutter scenarios experienced in bistatic passive radar. The effectiveness of the proposed scheme and its suitability for passive GMTI are demonstrated against both simulated and experimental data collected by a DVB-T-based multichannel mobile passive radar.

This work investigates the potentialities of a passive multidimensional ISAR imaging based on DVB-S transmitters of opportunity. Image fusion methods exploiting diversities in both the spatial and polarimetric domains are introduced, aiming at achieving an image with better quality than the images acquired by the individual observation angles and/or polarimetric channels. An analysis using experimental datasets comprising a passive receiver able to collect signals in both the horizontal and vertical polarizations, a cooperative turning ferry, and an Astra satellite has been provided.

Maritime airborne surveillance radars operating at high grazing angles experience significant sea clutter returns with a time and range-varying Doppler spectra, thus making the detection of small targets extremely difficult. Many target detection schemes assume models for the amplitude distribution that require estimation of specific parameters. These may not be accurate in all situations and hence reduce the detection performance. In this paper, we propose a new sea clutter suppression approach based on a dictionary learning strategy. The success of this data-driven approach is that it does not rely on statistical modeling of the clutter, but rather on the quality of the training data used to form the dictionary. Our analysis looks at the learning performance between batch and online strategies and then uses the obtained dictionaries to assess the clutter suppression capabilities in terms of improvement in the signal to interference ratio and the detection performance using a Monte Carlo analysis. To demonstrate these algorithms, data from the Australian Ingara L-band radar system has been used.

In recent years, passive radar has been investigated for airborne applications in imaging and detection of ground targets. There are challenges with detection of land targets from an airborne platform due to platform motion which causes the clutter Doppler to spread and the presence of discrete scatterers which can be strong and confused with targets of interest. In this paper, we compare two different detection schemes to assess their performance on a real airborne passive radar data from a land scene North of Poland. These include a standard coherent scheme and a sparse signal separation algorithm known as morphological component analysis. The performance is measured using a Monte Carlo simulation where synthetic targets are injected into the real data set.

Passive radar utilizes signals from broadcast, communication, or other transmitters of opportunity for the applications of target detection and imaging. For these applications knowledge of the transmitted signal for the correlation with the surveillance signal is a crucial factor. If digital signals are exploited for passive radar, it is possible to estimate and restore the transmitted signal. The error rate in the estimated transmitted signal is inversely related to the signal-to-noise ratio of the direct signal. The greater the amount of errors in the reconstructed signal, the worse become the correlation results in terms of a higher noise level due to side lobes and unwanted correlation artifacts. Therefore it is preferred to acquire a copy of the transmitted signal as clean as possible. The reference signal estimation capability can be improved by exploiting antenna diversity. In this paper we present the technique maximal ratio combining, which exploits the reception of multiple antennas to optimize the reference signal estimation. Here we also exploit both linear (vertical and horizontal) polarizations on receive to further improve the estimated reference signal. We show the improvement by using real data from an airborne passive radar system and by comparing the results of the antenna diversity approach to the results when using the reference signal from one antenna only.

Drones and unmanned aerial vehicles (UAVs) are increasingly popular, thus posing danger and threats to infrastructures and public safety. A technology for drone detection and classification would therefore significantly increase the level of security. In scenarios such as concerts, sport events, trade fairs, or in any situation where significant aggregation of people is present, such techniques should be non-invasive. That means they do not have to pose an additional threat to people themselves. To this end, passive radars offer an appealing solution, since they are able to offer a non-cooperative surveillance while not emitting any electromagnetic signal. On the contrary, they rely on existing transmitting infrastructure (also referred to as illuminators of opportunity, IoO), such as broadcasting signal sources (FM radio, terrestrial and satellite digital video broadcasting, cellular communication and so on). In this work, the possibility to exploit satellite television based passive radar for UAV detection is analyzed by experimental validation. In addition, micro-Doppler signatures for drones have been extracted, which might give information for subsequent UAV classification.

This paper focuses on range compression aspects to be considered in the signal processing of passive radars. In particular it focuses on passive radar systems mounted on moving platforms for ground moving target indication on the one hand and on synthetic-aperture radar on the other hand. As the signals of opportunity are not created for radar purposes, the underlying signal structure can lead to ambiguities and sidelobes and thus impede target detection or decrease the signal-to-noise ratio. Careful signal processing algorithms must be applied on the range compression stage in order to deal with these issues. Here we provide an overview of possible range compression techniques and give a suggestion which technique is the most appropriate depending on the type of application.

This paper shows a first analysis of polarimetric passive ISAR images using digital video broadcasting-satellite (DVB-S(2)) as illuminator of opportunity. A measurement campaign has been conducted exploiting an experimental system developed at Fraunhofer FHR and a ferry as cooperative target. The collected data have been firstly processed by means of backprojection to obtain ISAR images at each polarimetric channel. Then two different representations in the polarimetric domain are considered. The first one is a color coding based on a modified Pauli decomposition. The second one is the evaluation of the determinant of the Sinclair scattering matrix. From both representations we can recognize that different scattering mechanisms within the same target behave differently in the polarimetric domain. The analysis is conducted on two different data sets with distinct bistatic geometries. The retrieved results assess the usefulness of the polarimetric information in passive ISAR images.

This article addresses the problem of direct signal interference (DSI) and clutter cancellation for passive radar systems on moving platforms employing displaced phase centre antenna (DPCA) approach. Attention is focused on the development of signal processing strategies able to compensate for the limitations deriving from amplitude and phase imbalances that affect the two channels employed on receive. First, we show that using the signal received from the illuminator of opportunity as a source for channels calibration might be ineffective when DSI and clutter echoes have different directions of arrival, due to the effect of angle-dependent channel imbalance. Then, a two-stage strategy is proposed, consisting of a preliminary DSI removal stage at each receive channel, followed by a clutter-based calibration approach that basically enables an effective DPCA clutter suppression. Different strategies for channel calibration are proposed, aimed at compensating for potential angle and range-dependent channel errors, based on the maximization of the cancellation performance. Effectiveness of this scheme is shown against the experimental data from a DVB-T based moving passive radar, in the presence of both real and synthetic moving targets.

Over the last decades spaceborne synthetic aperture radar (SAR) has proved its capability as a remote sensing technique of great power and value. A number of precise SAR instruments (e.g., [1]-[4]) have been developed by space and defense agencies around the world and are being used today for a wide range of applications in wide-area land (e.g., [5]-[8]) and sea monitoring (such as [9]-[11]).

We investigate effects of transmitter imperfections in terms of time and frequency offsets on the performance of digital video broadcast-terrestrial based passive radars. To facilitate an accurate reconstruction of the transmitted waveform, transmitter imperfections need to be understood and compensated. The transmitter introduced clock imperfections are estimated and compensated via two different methods and tested on real-field measurements acquired in Germany and Australia for single frequency and multiple frequency networks.

This study investigates the causes and effects of signal mismatch on the performance of a passive bistatic radar that employs reference signal reconstruction processing on a moving receiver platform. In addition to the transmitter's imperfections, namely carrier frequency offset and sampling clock drift, motion induced Doppler is taken into consideration and compensated. Signal processing approaches are used that exploit the unique characteristics of the terrestrial digital video broadcast waveform in order to compensate for the combined effects of transmitter mismatch and the motion induced Doppler. The proposed methods are tested on real-field measurements acquired in Germany and Australia for single frequency network and multiple frequency network, respectively. The results demonstrate superior performance in terms of delay-Doppler discrimination.

In this chapter, the attention is turned toward multistatic passive radar systems on airborne platforms for the purpose of synthetic aperture radar (SAR) image creation. A passive radar system is a special type of bistatic radar that exploits noncooperative transmitters as its source of illumination. This chapter begins with an overview and introduction to passive SAR. By referring to the widely used digital video broadcast-terrestrial (DVB-T) standard as illuminator, we describe the complete signal processing chain in order to create a passive SAR image. This includes (i) preprocessing, which involves the synchronization, and the estimation of the reference signal; (ii) range compression, specifically addressing the time-varying waveform characteristics; (iii) the image formation stage, basically residing on back projection; and finally (iv) the issues related to mitigation of co-channel interference (CCI) arising in airborne passive radars.

A statistical analysis of clutter distribution supports the design and informs the performance of radar system. While extensive work on clutter statistics from monostatic radar systems has been performed, statistical analysis of passive bistatic radar clutter is limited. This paper presents the statistical analysis of clutter returns using a passive bistatic radar mounted on an airborne platform with a DVB-T illuminator of opportunity. In particular, the distributions of the data in-phase, quadrature and amplitude are investigated to understand different behaviours of the clutter. The fitting of Rayleigh, Weibull and Lognormal distributions to the clutter amplitude is the main focus of this initial analysis of clutter, collected from the airborne platform.

Continuous emission noise radars suffer from the problem of reduced sensitivity due to masking effects caused by the side-lobes of direct signal leakage, clutter returns and echoes of close targets. For noise radar on moving platforms the clutter returns are spread in Doppler, which makes the reduction of their masking effects challenging. Considering a single channel noise radar, conventional clutter suppression methods can not be applied, as only one degree of freedom is available. In order to cope with these issues the application of a modified extensive cancellation algorithm (ECA) for a single channel noise radar is proposed. The presented modification allows tailoring of the cancellation area to the shape of any clutter spread in range and Doppler. Successful masking effect reduction in a singlechannel noise radar on a moving platform is presented based on experimental data.

Passive radar systems on moving platforms suffer from Doppler-spread clutter that can mask moving targets of interest. Moreover, platform size restrictions further limit the number of antenna channels, which are needed to ameliorate the impacts of Doppler-spread clutter. However, an analysis of the clutter returns can potentially aid clutter cancellation. For this analysis, wavelet transforms (WT) are proposed to investigate different characteristics of clutter. A property of the WT is its ability to decompose signals at multiple scales, or resolutions, with an adaptive time window, compared to the Fourier transform and short time Fourier transform. A very different partitioning of the WT reveals different characteristics and information of signals which can potentially lead to the target signal being better distinguished. The paper also investigates a sparse signal separation method using tunable Q-factor wavelet transforms to extract target signals from clutter for a passive radar on moving platforms exploiting DVB-T transmissions.

Passive radar has reached a stage of maturity such that it can be mounted on mobile platforms for the purpose of moving-target-detection. However some constraints limit the capability of target detection within the Doppler spread clutter region which arises due to the receiver's movement. Typically employed terrestrial illuminators of opportunity transmit in the Very High Frequency/Ultra High Frequency band, which puts some constraints on the size and number of employed antenna elements. If two antenna elements are employed, the Displaced Phase Center Antenna (DPCA) approach provides a meaningful possibility to suppress the clutter. However, the performance of this clutter suppression technique is severely degraded in case of non-ideal DPCA condition or if the employed channels are not properly calibrated. Here we suggest a technique to re-establish inter-channel calibration based on the Minimum Variance clutter power spectrum estimation. Specifically, we regard the technique as a dedicated adaptive digital calibration stage in order to improve clutter cancellation. The validity of the proposed approach is tested against real data, showing improved clutter cancellation capability.

This paper addresses the problem of direct signal interference (DSI) and clutter cancellation for passive radar systems on moving platforms using displaced phase centre antenna (DPCA) approach in the presence of receive channels imbalance. First, we show that using the signal emitted by the illuminator of opportunity as a source for channels calibration might be ineffective when DSI and clutter echoes have different directions of arrival. Then, a calibration approach is presented, based on supervised selection of clutter areas in the range-Doppler map. Finally, a two-stage strategy is presented, composed of an ECA-based DSI removal prior to DPCA clutter cancellation, which doesn't require supervised selection of the calibration area. The effectiveness of this scheme in the joint suppression of DSI and clutter is shown against real data.

This work presents an analysis of passive inverse synthetic aperture radar images obtained exploiting simultaneously digital video broadcasting-terrestrial (DVB-T) and digital video broadcasting-satellite (DVB-S) as illuminators of opportunity (IOs) over a cooperative maritime target with known motion. The combined exploitation of these two IOs is extremely appealing for passive imaging purposes, given their complementary characteristics. The analysis is first conducted in a simulated environment, to show the different expected outcomes from the two considered bistatic geometries and operating bandwidths. Subsequently, the same analysis is repeated over real data acquired during a field trial, by exploiting experimental setups developed at Fraunhofer FHR. In particular, DVB-T and DVB-S data are focused by means of back projection, which enables an easier comparison of the different ISAR products. Real data results show good match with simulated ones. Target size can be estimated with good accuracy in both DVB-T and DVB-S cases, and dominant scatterers can also be identified. DVB-S also enables target-shape recognition, given its higher signal bandwidth.