Accurate Detection of Multiple Targets by Uniform Rectangular Array Radar With Threshold Soft Update and Area Rescanning

Abstract

Background. If the intensity of moving targets within a surveyed area is low, an optimal number of uniform rectangular array (URA) radar sensors is in either the minimally-sized URA (or close to it) or maximally-sized URA (or close to it), where the URA size is regulated by (symmetrically) turning off vertical and horizontal sensors. However, this does not guarantee detection of any target because sometimes the threshold detection, by which the main parameters of a pair of two targets are estimated, fails even by using the soft threshold approach when the threshold is gradually decreased while the detection fails.
 Objective. In order to improve detection of multiple ground-surface targets by a URA radar, the goal is to decrease a number of detection fails, when targets are just missed. For this, the approach of threshold soft update and a set of quasioptimal URA sizes included and URAs are to be used by rescanning the area if the detection fails.
 Methods. To achieve the goal, the functioning of the URA radar is simulated for a set of randomly generated targets, where roughly a half of the set is to be of single targets, and the other half is to be of pairs of targets. The simulation is configured and carried out by using MATLAB® R2021b Phased Array System ToolboxTM functions based on a model of the monostatic radar.
 Results. Neither the soft threshold approach, nor the rescanning increase the detection accuracy. However, when either the soft threshold or rescanning is applied, or they both are applied, the number of detections is increased. The increment can be evaluated in about 2.7 %, but the expected high-accurate detection performance slightly drops. This is caused by that the soft thresholding and rescanning attempt at retrieving at least some information about the target instead of the detection fail.
 Conclusions. Using the threshold soft update approach along with a more frequent rescanning decreases a number of detection fails. Besides, the soft thresholding and rescanning allow slightly decreasing the number of URA sensors sufficient to maintain the same detection accuracy by increasing the averaged number of single-target and two-target detections at least by 2.5 %. The increment in a number of detected targets on average is equivalent to increasing the probability of detection.

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