Direct-Path Interference and Noise Resistant Signal Detection and Estimation for Passive Sensin

Passive sensing has been employed in radar, underwater acoustics, seismology, and others. Fueled by the proliferation of wireless networks and devices, recent years have witnessed interest in a variety of emerging applications of passive sensing, e.g., using TV, cellular, or WiFi signals for home-based health monitoring, intruder detection, indoor tracking, etc. However, conventional passive signal processing techniques are sensitive to noise and interference inherent in passive sensing systems. This dissertation develops a series of new passive signal detection and estimation methods that are resistant to such impairments.;First, we consider the problem of joint delay-Doppler estimation of a moving target in passive radar that employs a non-cooperative illuminator of opportunity (IO), a reference channel (RC) to obtain a reference signal, and a surveillance channel (SC) for target monitoring. We consider a practically motivated scenario where the RC receives a noise-contaminated copy of the IO signal and the SC observation is polluted by a residual direct-path interference (DPI) that is usually neglected by prior studies. We propose an expectation-maximization (EM) based estimator and a modified cross-correlation (MCC) estimator. In addition, we derive the Cramer-Rao lower bound for the estimation problem. Second, the target detection problem in multistatic passive radar is examined. We explicitly consider the effect of the residual DPI and develop two new detectors. Another contribution is that the proposed detectors exploit the correlation of the IO waveform for passive detection. Proposed detectors are developed within generalized likelihood ratio test (GLRT) framework, which involves nonlinear estimation that is solved using EM algorithm. Last, a parametric approach is proposed by modeling the unknown signal transmitted from the IO as an auto-regressive (AR) process whose temporal correlation is jointly estimated and exploited for passive detection. The detection problem is formulated for multistatic passive radar where receivers are contaminated by non-negligible noise and DPI. The proposed solution is developed based on the GLRT principle and the EM algorithm. In addition, we extend several conventional passive detectors to provide them with an ability to handle the DPI problem. A clairvoyant matched filtering detector is derived as well assuming the knowledge of the IO waveform.