Multitarget Resolution and Performance for Radar Sensor Network (RSN)

Multitarget detection and separation are important for radar sensor network (RSN). Since the interference among the targets existing in adjacent resolution cells may mask the desired one, in this paper we develop a multitarget resolution model for RSN systems. Three waveforms, i.e., simple pulse, linear frequency modulated (LFM) pulse and Barker codes (phase modulated pulse) are applied to appraise the resolution performance. The multitarget detection performance of a distributed RSN over pass-loss fading channels with additive noise has also been analyzed. For fusion center we use Likelihood ratio (LR) decision rule, which is reduced to the test statistics according to the channel signal-to-noise ratio (SNR), probability of false alarm and the number of radar sensors (RSs). Simulation results demonstrate that detection and resolution performances are better with higher SNR. Adding the number of RSs in RSN can improve the performance, combination of amplifying SNR and increasing the number of RSs can get a much better RSN system performance, while increasing targets can exert worse influence on the detection results.