Moving target indication

About: Moving target indication is a research topic. Over the lifetime, 2653 publications have been published within this topic receiving 32435 citations.

SAR based adaptive GMTI

Abstract: We consider ground moving target indication (GMTI) and target velocity estimation based on multi-channel synthetic aperture radar (SAR) images. Via forming velocity versus cross-range images, we show that small moving targets can be detected even in the presence of strong stationary ground clutter. Moreover, the velocities of the moving targets can be estimated, and the misplaced moving targets can be placed back to their original locations based on the estimated velocities. Adaptive beamforming techniques, including Capon and generalizedlikelihood ratio test (GLRT), are used to form velocity versus cross-range images for each range bin of interest. The velocity estimation ambiguities caused by the multi-channel array geometry are analyzed. We also demonstrate the effectiveness of our approaches using the Air Force Research Laboratory (AFRL) publicly-released Gotcha SAR based GMTI data set.

An experimental study on image based multi-channel SAR-GMTI algorithm

Abstract: The authors have recently proposed an algorithm for target detection and velocity estimation for multi-channel SAR-GMTI (Synthetic Aperture Radar - Ground Moving Target Indication) systems [1]. The proposed algorithm is a combination of extensions of DPCA (Displaced Phase Center Antenna) and ATI (Along Track Interferometry). In this paper, we report some results obtained from an airborne three-channel SAR experiment to show the potentials of the proposed algorithms.

On A Nascent Mathematical-Physical Latency-Information Theory, Part I: The Revelation Of Powerful And Fast Knowledge-Unaided Power-Centroid Radar

Abstract: In this first part of the latest latency-information theory (LIT) and applications paper series powerful and fast 'knowledge-unaided' power-centroid (F-KUPC) radar is revealed. More specifically, it is found that for real-world airborne moving target indicator radar subjected to severely taxing environmental conditions F-KUPC radar approximates the signal to interference plus noise ratio (SINR) radar performance derived with more complex knowledge-aided power-centroid (KAPC) radar. KAPC radar was discovered earlier as part of DARPA's 2001-2005 knowledge-aided sensor signal processing expert reasoning (KASSPER) Program and outperforms standard priorknowledge radar schemes by several orders of magnitude in both the compression of sourced intelligence-space of priorknowledge, in the form of SAR imagery, and the compression of processing intelligence-time of the associated clutter covariance processor, while also yielding an average SINR radar performance that is approximately 1dB away from the optimum. In this paper, it is shown that the average SINR performance of significantly simpler F-KUPC radar emulates that of KAPC radar and, like KAPC radar, outperforms a conventional knowledge-unaided sample covariance matrix inverse radar algorithm by several dBs. The matlab simulation programs that were used to derive these results will become available in the author's Web site.

Wigner-Ville distribution: an important functional block for radar target detection in clutter

Abstract: In this paper we describe an application of the Wigner-Ville distribution (WVD) for the detection of a radar target signal buried in a strong clutter background. The WVD transforms the received radar signal into a time-frequency image that accounts for the nonstationary nature of the radar signal. The cross-terms, an inherent feature of the WVD, play a constructive role in this application. In particular, their presence enhances the visibility of a target in the WVD image in a unique and significant way. The WVD image provides a common input to a pair of channels, with one channel matched to clutter and the other channel matched to target plus clutter. Each channel consists of a principal components analyzer (for feature extraction) followed by a multilayer perceptron classifier. Experimental results, based on real-life, radar data, are presented to demonstrate the superior performance of the new detection strategy compared to a conventional constant false-alarm rate (CFAR) processor. >

Frequency‐based target localization methods for widely separated MIMO radar

Abstract: Frequency-based localization methods are widely used to find emitter locations. Several techniques are described in the literature for emitter localization based on Doppler frequency shifts. These techniques can be used efficiently for emitter localization by using narrowband signals. Although these methods are simple and efficient, the application to the radar systems for target localization is very limited. In this paper, a new low-complexity target localization method, Target Localization via Doppler Frequencies (TLDF), for Doppler-only Multi-Input, Multi-Output (MIMO) radar with widely separated stations is described. By using widely separated MIMO radars with unmodulated continuous wave signals, the received frequencies and the Doppler shifts can be estimated efficiently. The position and the velocity of the target can be found from these estimated frequencies by a search in the position space. As the Doppler frequency is estimated efficiently, not only the target velocity but also the direction of the target is estimated accurately with the TLDF method. The Cramer-Rao Bounds (CRB) are calculated for the target velocity and the target position estimations in two-dimensional space. In simulations, the proposed method is compared with the iso-Doppler curves-based traditional method and with the CRB for different geometries. The performance of the proposed method is not affected from the target amplitude fluctuations because of its frequency-based nature. Finally, the comparison between the frequency-only MIMO radar and the pulsed monostatic radar is investigated, and the simplicity and the efficiency of the proposed method are demonstrated.