Maximum likelihood geolocation and track initialization using a ground moving target indicator (GMTI) report

Mahendra Mallick

doi:10.1117/12.666464

19 May 2006 Maximum likelihood geolocation and track initialization using a ground moving target indicator (GMTI) report

Mahendra Mallick

Author Affiliations +

Proceedings Volume 6236, Signal and Data Processing of Small Targets 2006; 62360D (2006) https://doi.org/10.1117/12.666464
Event: Defense and Security Symposium, 2006, Orlando (Kissimmee), Florida, United States

Abstract

The GMTI radar sensor plays an important role in surveillance and precision tracking of ground moving targets. A class of GMTI sensors which employs a linear antenna measures the range, path difference between the received beams, and range-rate. The path difference is equivalent to the cone angle between the axis of the antenna and the radar line-of-sight. The measurement errors for the range, cone angle, and range-rate are independent. The measurements for the conventional GMTI measurement model are range, azimuth, and range-rate. The azimuth is a derived measurement obtained from the range and cone angle measurements. Therefore, the errors in the range and azimuth are correlated. However, the conventional GMTI measurement model ignores this correlation. We derive an analytic expression for the cross-covariance between the range and azimuth errors and show that the cross-covariance is inversely proportional to the ground-range. Thus for a stand-off GMTI sensor, the approximation used in neglecting the cross-covariance is reasonable. We present a new algorithm for the geolocation of the target using the maximum likelihood estimator and range, cone angle, and surface height measurements. Along-track, cross-track, and vertical errors in the sensor position and errors in the antenna orientation are taken into account. We use a flat Earth approximation. An initial estimate of the target state and associated covariance are required in a tracking filter using the first GMTI report. We present an extended Kalman filter based algorithm for GMTI track initialization using the GMTI geolocation results. Numerical results are presented using simulated data.

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Mahendra Mallick "Maximum likelihood geolocation and track initialization using a ground moving target indicator (GMTI) report", Proc. SPIE 6236, Signal and Data Processing of Small Targets 2006, 62360D (19 May 2006); https://doi.org/10.1117/12.666464

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KEYWORDS

Sensors

Antennas

Error analysis

Radar

Detection and tracking algorithms

Radar sensor technology

3D acquisition

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