Wide-Angle Multistatic Synthetic Aperture Radar: Focused Image Formation and Aliasing Artifact Mitigation

Traditional monostatic Synthetic Aperture Radar (SAR) platforms force the user to choose between two image types: larger, low resolution images or smaller, high resolution images. Switching to a Wide-Angle Multistatic Synthetic Aperture Radar (WAM-SAR) approach allows formation of large high-resolution images. Unfortunately, WAM-SAR suffers from two significant implementation problems. First, wavefront curvature effects, non-linear flight paths, and warped ground planes lead to image defocusing with traditional SAR processing methods. A new 3-D monostatic/bistatic image formation routine solves the defocusing problem, correcting for all relevant wide-angle effects. Inverse SAR (ISAR) imagery from a Radar Cross Section (RCS) chamber validates this approach. The second implementation problem stems from the large Doppler spread in the wide-angle scene, leading to severe aliasing problems. This research effort develops a new anti-aliasing technique using randomized Stepped-Frequency (SF) waveforms to form Doppler filter nulls coinciding with aliasing artifact locations. Both simulation and laboratory results demonstrate effective performance, eliminating more than 99% of the aliased energy

Two-Dimensional Imaging Algorithm Based on Linear Prognosis for Space Target in Bistatic ISAR System

In bistatic inverse synthetic aperture radar (Bi-ISAR) system, its image resolution is lower than monostatic ISAR system. In order to solve this problem, the linear prognosis algorithm is adopted in the imaging process and the imaging algorithm based on linear prognosis is proposed. Space target Bi-ISAR imaging is taken as example in the research. The one-dimensional range profile is created through pulse compression method. Before the azimuth compression, burg entropy maximum algorithm in Levions recursive method is used to estimate the prognosis coefficients and the azimuth echo data. Then Fourier transformation is used to compress the azimuth data in order to get the high resolution azimuth image. This imaging method can obtain the two-dimensional image with the resolution equal to the monostatic ISAR or even higher than it. Simulation experiments have verified the effectiveness and availability of the algorithm

GNSS-based passive radar techniques for maritime surveillance

The improvement of maritime traffic safety and security is a subject of growing interest, since the traffic is constantly increasing. In fact, a large number of human activities take place in maritime domain, varying from cruise and trading ships up to vessels involved in nefarious activities such as piracy, human smuggling or terrorist actions. The systems based on Automatic Identification System (AIS) transponder cannot cope with non-cooperative or non-equipped vessels that instead can be detected, tracked and identified by means of radar system. In particular, passive bistatic radar (PBR) systems can perform these tasks without a dedicated transmitter, since they exploit illuminators of opportunity as transmitters. The lack of a dedicated transmitter makes such systems low cost and suitable to be employed in areas where active sensors cannot be placed such as, for example, marine protected areas. Innovative solutions based on terrestrial transmitters have been considered in order to increase maritime safety and security, but these kinds of sources cannot guarantee a global coverage, such as in open sea. To overcome this problem, the exploitation of global navigation satellites system (GNSS) as transmitters of opportunity is a prospective solution. The global, reliable and persistent nature of these sources makes them potentially able to guarantee the permanent monitoring of both coastal and open sea areas. To this aim, this thesis addresses the exploitation of Global Navigation Satellite Systems (GNSS) as transmitters of opportunity in passive bistatic radar (PBR) systems for maritime surveillance. The main limitation of this technology is the restricted power budget provided by navigation satellites, which makes it necessary to define innovative moving target detection techniques specifically tailored for the system under consideration. For this reason, this thesis puts forward long integration time techniques able to collect the signal energy over long time intervals (tens of seconds), allowing the retrieval of suitable levels of signal-to-disturbance ratios for detection purposes. The feasibility of this novel application is firstly investigated in a bistatic system configuration. A long integration time moving target detection technique working in bistatic range&Doppler plane is proposed and its effectiveness is proved against synthetic and experimental datasets. Subsequently the exploitation of multiple transmitters for the joint detection and localization of vessels at sea is also investigated. A single-stage approach to jointly detect and localize the ship targets by making use of long integration times (tens of seconds) and properly exploiting the spatial diversity offered by such a configuration is proposed. Furthermore, the potential of the system to extract information concerning the detected target characteristics for further target classification is assessed

Active and Passive Multi-Sensor Radar Imaging Techniques Exploiting Spatial Diversity

The work here presented reports several innovative SAR and ISAR radar imaging techniques exploiting the spatial diversity offered by multi-sensor systems in order to improve the performance with respect to the conventional, single channel cases. Both the cases of dedicated transmitters and exploitation of opportunity transmitters are considered

Active and Passive Multi-Sensor Radar Imaging Techniques Exploiting Spatial Diversity

The work here presented reports several innovative SAR and ISAR radar imaging techniques exploiting the spatial diversity offered by multi-sensor systems in order to improve the performance with respect to the conventional, single channel cases. Both the cases of dedicated transmitters and exploitation of opportunity transmitters are considered

Innovative SAR & ISAR Signal Processing

This thesis reports on research into the eld of Synthetic Aperture Radar (SAR) and Inverse Synthetic Aperture Radar (ISAR) signal processing. The contributions of this thesis may be divided into two following parts: A new bistatic 3D near eld circular SAR imaging algorithm was devel- oped. High resolution radar imaging is typically obtained by combining wide bandwidth signals and synthetic aperture processing. High range resolution is obtained by using modulated signals whereas high cross range resolution is achieved by coherently processing the target echoes at dierent aspect angles of the target. Anyway, theoretical results have shown that when the aspect angle whereby the target is observed is suf- ciently wide, high resolution target images can be obtained by using continuous wave (CW) radars [2], therefore allowing to reduce hardware costs. In a similar way, three dimensional radar imaging can be per- formed by coherently processing the backscattered eld as a function of two rotation angles about two orthogonal axes [3].Three dimensional tar- get radar imaging can be eciently obtained by means of a 3D Fourier Transform, when the far-eld (planar wave) approximation holds. Oth- erwise, the wavefront curvature has to be accounted for. For this reason, a new algorithm based on a near eld spherical wave illumination that takes into account the wavefront curvature by adopting a planar piece- wise approximation was designed. This means that the wavefront is as- sumed to be locally planar around a given point on the target. The oper- ator that the algorithm uses for the focusing procedure is a space variant focusing function which aims at compensating the propagation losses and the wavefront curvature. The algorithm has been developed under the Microwave Electronic Imaging Security and Safety Access (MELISSA) project. The system MELISSA is a body scanner whose purpose is the detection of concealed objects. The added value of the system is the capability to provide an electromagnetic image of the concealed objects. The author would like to thank all people that worked at the project, all LabRass colleagues, all people who designed and acquired real data, all people that permitted the drafting of the rst part of this thesis. The developed algorithm was presented in the chapter 1. The goal of this work was the system design concerning the imaging point of view, by simulating and therefore predicting the system performance by means of the developed algorithm. In the chapter 2 was shown how the design was achieved. Finally, in the chapter 3, the results on real data measured in anechoic chamber with a system with characteristics very close to the nal system prototype MELISSA, was presented. A new way of ISAR processing has been dened, by applying the tradi- tional ISAR processing to data acquired from passive radars. Purpose of the ISAR processing is to extract an electromagnetic bi-dimensional im- age of the target in order to determine the main geometric features of the target, allowing (when possible) recognition and classication. Passive radars are able to detect and track targets by exploiting illuminators of opportunity (IOs). In this work of thesis, it will be proven that the same concept can be extended to allow for Passive Inverse Synthetic Aperture Radar (P-ISAR) imaging. A suitable signal processing is detailed that is able to form P-ISAR images starting from range-Doppler maps, which represent the output of a passive radar signal processing. Multiple chan- nels Digital Video Broadcasting - Terrestrial (DVB-T) signals are used to demonstrate the concept as they provide enough range resolution to form meaningful ISAR images. The problem of grating lobes, generated by DVB-T signal, is also addressed and solved by proposing an innovative P-ISAR technique. The second part of this thesis has been developed un- der the Array Passive ISAR adaptive processing (APIS) project. APIS is dened as a multichannel, bi-static single receiver for array passive radar, capable of detecting targets and generating ISAR images of the detected targets for classication purposes. The author would like to thank all people that worked at the project, all LabRass colleagues, all people who designed, built the prototype and acquired real data, all people that per- mitted the drafting of the second part of this thesis. In the chapter 4, the basics on Passive Bistatic Radar (PBR) was brie y recalled, the P-ISAR processor was detailed and the new algorithm per the Grating Lobes Cancellation was presented. In the chapter 5, some numerical results on simulated data was shown, in order to demonstrate the potentiality of the P-ISAR, for the imaging and classication purpose. In fact, by using more than three adjacent channels and by observing the signal for a long time, ner range and cross-range resolutions, respectively, could be achieved. Finally, the obtained results on real data was discussed in the chapter 6

Decentralized approach for translational motion estimation with multistatic inverse synthetic aperture radar systems

This paper addresses the estimation of the target translational motion by using a multistatic Inverse Synthetic Aperture Radar (ISAR) system composed of an active radar sensor and multiple receiving-only devices. Particularly, a two-step decentralized technique is derived: the first step estimates specific signal parameters (i.e., Doppler frequency and Doppler rate) at the single-sensor level, while the second step exploits these estimated parameters to derive the target velocity and acceleration components. Specifically, the second step is organized in two stages: the former is for velocity estimation, while the latter is devoted to velocity estimation refinement if a constant velocity model motion can be regarded as acceptable, or to acceleration estimation if a constant velocity assumption does not apply. A proper decision criterion to select between the two motion models is also provided. A closed-form theoretical performance analysis is provided for the overall technique, which is then used to assess the achievable performance under different distributions of the radar sensors. Additionally, a comparison with a state-of-the-art centralized approach has been carried out considering computational burden and robustness. Finally, results obtained against experimental multisensory data are shown confirming the effectiveness of the proposed technique and supporting its practical application

Passive radar based on WiFi transmissions: signal processing schemes and experimental results

Aim of this work is to study innovative techniques and processing strategies for a new passive sensor for short range surveillance. The principle of work of the sensor will be based on the passive radar principle, and WiFi transmissions - which usually provide Internet access within local areas - will be exploited by the passive sensor to detect, localize and classify targets

Passive radar based on WiFi transmissions: signal processing schemes and experimental results

Aim of this work is to study innovative techniques and processing strategies for a new passive sensor for short range surveillance. The principle of work of the sensor will be based on the passive radar principle, and WiFi transmissions - which usually provide Internet access within local areas - will be exploited by the passive sensor to detect, localize and classify targets