A Sparsity-Based Passive Multistatic Detector.

In this paper, we examine the problem of target detection for the multistatic passive radar. Passive radar systems leverage the existing wireless sources, such as radio/TV stations and cellular signals that are referred to as illuminators of opportunity (IOs), to illuminate the environment and provide surveillance functions. Usually, these IO source signals are sparse or locally sparse in the frequency domain. We develop a passive multistatic detector by exploiting the sparsity or local sparsity of the IO signals. To improve the computational efficiency, two fast implementations of the proposed detector are also introduced. Simulation results show that the proposed approaches outperform the conventional passive detection methods that model the IO signals as unknown without any specific structures. [ABSTRACT FROM AUTHOR]