Paper
28 April 2010 Target localization in moving radar platform exploiting range and Doppler information through semidefinite relaxation
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Abstract
Moving radar platforms form synthetic apertures for effective target localization. One of the important target localization techniques is to multilaterate the position of a target based on the own positions of the radar and the range estimates obtained at each radar position. In practical applications, the radar positions as well as the range estimates are subject to error due to maneuvering, timing error, as well as measurement noise. Previous works have shown that, by incorporating the semidefinite relaxation techniques which permit the use of convex optimization approaches to solve a large class of nonconvex estimation problems, improved target location estimates can be achieved over those obtained from conventional techniques, such as least square methods. In some radar applications, on the other hand, it may be advantageous to incorporate the Doppler measurements. Doppler frequency information is often complementary to range measurements in target localization and is particularly helpful when range information alone does not provide satisfactory target localization performance. In this paper, we consider the problem of target localization based on both range and Doppler estimates obtained at multiple radar locations, where such information as well as the radar locations are subject to certain random errors. Semidefinite relaxation is applied to formulate convex solutions for this problem. Simulation results are provided to demonstrate performance improvement by utilizing both range and Doppler estimates.
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Jia Liu, Yimin D. Zhang, and Moeness G. Amin "Target localization in moving radar platform exploiting range and Doppler information through semidefinite relaxation", Proc. SPIE 7706, Wireless Sensing, Localization, and Processing V, 77060E (28 April 2010); https://doi.org/10.1117/12.850856
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KEYWORDS
Doppler effect

Radar

Sensors

Error analysis

Algorithm development

Convex optimization

Receivers

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