Articles | Volume 15
Adv. Radio Sci., 15, 69–76, 2017
https://doi.org/10.5194/ars-15-69-2017
Adv. Radio Sci., 15, 69–76, 2017
https://doi.org/10.5194/ars-15-69-2017

  21 Sep 2017

21 Sep 2017

Sparse representation discretization errors in multi-sensor radar target motion estimation

Hossein Azodi, Uwe Siart, and Thomas F. Eibert Hossein Azodi et al.
  • Chair of High-Frequency Engineering, Department of Electrical and Computer Engineering, Technical University of Munich, 80290 Munich, Germany

Abstract. In a multi-sensor radar for the estimation of the targets motion states, more than one module of transmitter and receiver are utilized to estimate the positions and velocities of targets, also known as motion states. By applying the compressed sensing (CS) reconstruction algorithms, the surveillance space needs to be discretized. The effect of the additive errors due to the discretization are studied in this paper. The errors are considered as an additive noise in the well-known under-determined CS problem. By employing properties of these errors, analytical models for its average and variance are derived. Numerous simulations are carried out to verify the analytical model empirically. Furthermore, the probability density functions of discretization errors are estimated. The analytical model is useful for the optimization of the performance, the efficiency and the success rate in CS reconstruction for radar as well as many other applications.

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Short summary
This work investigates the errors, numerically and analytically, which occur due to the discretization of surveillance space in a multi-sensor radar system. The result of these investigations help to imprve the efficiency of the well-known compressed sensing algorithms. The improvement is critical for the cases where the signal processing algorithms must deliver the results within very short time intervals, e.g. 5 milliseconds or less.