Application and extension of space-time adaptive processing to passive FM radar

We are working on advanced signal processing techniques for passive radar applications. Recent experiments with passive radar have proved that passive radar method is promising as a supplement to the conventional radar technique. Passive radar utilizes commercial radio or TV broadcasting signals to detect targets. To work properly, passive radar systems require at least two synchronized receivers: a reference receiver and a target receiver. Due to the unsupervised radio broadcasts, data quality and imaging resolution is limited since the received reference signal is distorted because of multipath propagation. At the target receiver, interference and ground clutter further degrade radar's resolution.; We recently redesigned our system, improving upon the first generation passive VHF radar. The center piece of the new receiver system is a newly developed software-defined-radio, or digital receiver. The improved system is more flexible and may be easily reconfigured according to the radio environment and desired data pattern for processing and targets.; To correct the multipath distortion of reference signal, blind equalization techniques are investigated, specifically on FM broadcasting signal which is analog-modulated and short-time correlated. In order to achieve ‘perfect-recovery’, fractionally spaced equalization (FSE) with the constant modulus criterion for FM radio signal is developed and investigated experimentally as well as theoretically.; We are developing a subtraction algorithm to extract very weak signals in the case of strongly independent observation of illumination. In a bi-static passive radar, both ground clutter and interference will dominate radar imaging. Instead of using a sensor array, this algorithm will adaptively remove the ground clutter component from the scattered signal with availability of the clean reference signal. Interference is also removed by recursively applying this subtraction algorithm provided the availability of the interference source. Adaptive Least Mean Square (LMS) is the core of this algorithm. An optimal step size for LMS algorithm in passive FM radar is proposed.