Detection and parameter estimation of manoeuvring targets with passive bistatic radar

Malanowski, Mateusz

doi:10.1049/iet-rsn.2012.0072

Cited by 43 publications

(24 citation statements)

References 9 publications

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“…By performing a cross-correlation operation between the direct path signal and the target echoes, the time delay (TD) could be measured, which holds information about the unknown target position. By multiplying with the signal propagation speed, the TD can be directly converted into the bistatic range (BR) [7]. Each BR measurement traces out an ellipsoid equation, with its foci located at the transmitter and the receiver positions.…”

Section: Introductionmentioning

confidence: 99%

Refining Inaccurate Transmitter and Receiver Positions Using Calibration Targets for Target Localization in Multi-Static Passive Radar

Zhao

Liu

et al. 2019

Sensors

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Transmitter and receiver position errors have been known to significantly deteriorate target localization accuracy in a multi-static passive radar (MPR) system. This paper explores the use of calibration targets, whose positions are known to the MPR system, to counter the loss in target localization accuracy arising from transmitter/receiver position errors. This paper firstly evaluates the Cramér–Rao lower bound (CRLB) for bistatic range (BR)-based target localization with calibration targets, which analytically indicates the potential of calibration targets in enhancing localization accuracy. After that, this paper proposes a novel closed-form solution, which includes two steps: calibration step and localization step. Firstly, the calibration step is devoted to refine the inaccurate transmitter and receiver locations using the BR measurements from the calibration targets, and then in the calibration step, the target localization can be accurately achieved by using the refined transmitter/receiver positions and the BR measurements from the unknown target. Theoretical analysis and simulation results indicate that the proposed method can attain the CRLB at moderate measurement noise level, and exhibits the superiority of localization accuracy over existing algorithms.

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Section: Introductionmentioning

confidence: 99%

Refining Inaccurate Transmitter and Receiver Positions Using Calibration Targets for Target Localization in Multi-Static Passive Radar

Zhao

Liu

et al. 2019

Sensors

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“…In the last 60 years, radars can be classified into surface-based (ground-based and sea-based, including vehicle-borne and ship-based) radar, airborne radar and space-based radar, according to the installation or platform [1,2]. As a supplemental installation, near-space vehicle-borne radars have ignited great interest for surveillance applications in recent years [3,4,5,6]. For surveillance purposes, a near-space vehicle-borne radar has many advantages to be addressed:

Compared to a surface-based radar, the near-space vehicle-borne radar has wide coverage, as it is capable of the surveillance of extremely large areas [5,7].

…”

Section: Introductionmentioning

confidence: 99%

Performance Evaluation of Target Detection with a Near-Space Vehicle-Borne Radar in Blackout Condition

Wang

et al. 2016

Sensors

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Radar is a very important sensor in surveillance applications. Near-space vehicle-borne radar (NSVBR) is a novel installation of a radar system, which offers many benefits, like being highly suited to the remote sensing of extremely large areas, having a rapidly deployable capability and having low vulnerability to electronic countermeasures. Unfortunately, a target detection challenge arises because of complicated scenarios, such as nuclear blackout, rain attenuation, etc. In these cases, extra care is needed to evaluate the detection performance in blackout situations, since this a classical problem along with the application of an NSVBR. However, the existing evaluation measures are the probability of detection and the receiver operating curve (ROC), which cannot offer detailed information in such a complicated application. This work focuses on such requirements. We first investigate the effect of blackout on an electromagnetic wave. Performance evaluation indexes are then built: three evaluation indexes on the detection capability and two evaluation indexes on the robustness of the detection process. Simulation results show that the proposed measure will offer information on the detailed performance of detection. These measures are therefore very useful in detecting the target of interest in a remote sensing system and are helpful for both the NSVBR designers and users.

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“…Passive radars often use IOs in the VHF/UHF band, which is usually not available for active radars. Most of the current studies on passive radar involve target detection and tracking using different kinds of IOs, such as FM radio, wireless local area network signals, and digital video broadcasting-terrestrial (DVB-T) signals [3][4][5][6]. Among these candidates, DVB-T signals use digital waveforms employing a coded orthogonal frequency division multiplex modulation [7] and therefore display more attractive ambiguity function properties over conventional analog signals [8].…”

Section: Introductionmentioning

confidence: 99%

Compressive sensing–based algorithm for passive bistatic ISAR with DVB-T signals

Qiu

Giusti

Bacci

et al. 2015

IEEE Trans. Aerosp. Electron. Syst.

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Inverse synthetic aperture radar (ISAR) images can be obtained using digital video broadcasting-terrestrial (DVB-T)-based passive radars. However, television broadcast-transmitted signals offer poor range resolution for imaging purposes, because they have a narrower bandwidth with respect to those transmitted by a dedicated ISAR system. To reach finer range resolutions, signals composed of multiple DVB-T channels are required. Problems arise, however, because DVB-T channels are typically widely separated in the frequency domain. The gaps between channels produce high grating Manuscript lobes in the image domain when Fourier-based algorithms are used to form the ISAR image. In this paper, compressive sensing theory is investigated to address this problem because of its ability to reconstruct sparse signals by using incomplete measures. By solving an optimization problem under the constraint of signal sparsity, passive ISAR images can be obtained with strongly reduced grating lobes. Both simulation and experimental results are shown to demonstrate the validity of the proposed approach.

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Detection and parameter estimation of manoeuvring targets with passive bistatic radar

Cited by 43 publications

References 9 publications

Refining Inaccurate Transmitter and Receiver Positions Using Calibration Targets for Target Localization in Multi-Static Passive Radar

Refining Inaccurate Transmitter and Receiver Positions Using Calibration Targets for Target Localization in Multi-Static Passive Radar

Performance Evaluation of Target Detection with a Near-Space Vehicle-Borne Radar in Blackout Condition

Compressive sensing–based algorithm for passive bistatic ISAR with DVB-T signals

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