LAUSR

Compressive sensing (CS) theory have been proposed in the field of radar for target detection. The challenge of CS applied to passive bistatic radar (PBR) lies in the high-computational complexity aggravated by the transmitted signal dependent time-varying sparse model. So, we propose a transmitted-signal-free and time-invariant sparse model for passive radar based on orthogonal frequency division multiplexing waveforms. We first generate the sparse model using the surveillance signal and pilot information only, and exploiting the sparsity of scene including only a few targets and clutter. Then, range-Doppler profile for target detection can be implemented based on our proposed sparse model. Finally, simulation and experimental results illustrate that our proposed sparse model has high detection performance.