No abstract

In recent years, researchers have addressed the problem of using noncoherent approaches to estimate pulse width and pulse repetition interval. Since the measured transmitter is noncooperative, and noncoherent integration gain can be realized, the input signal-to-noise ratio (SNR) for these estimators becomes critical. We examine multiple edge detectors that exploit moving sums calculated as part of a Haar filtering of the received signal magnitudes. Two different ratio tests are considered in addition to the Haar filtering (or "difference of boxes") approach, and a binary hypothesis test is designed based on a "smallest of" constant false alarm rate formulation. Probability arguments are then invoked to derive readily evaluated expressions for the detection thresholds. Tests are conducted, indicating that performance of the ratio-based approaches is comparable in terms of processed peak-to-background ratio. However, comparisons of root mean-squared (RMS) error indicate that the difference-based (Haar) approach produces lower error than both ratio-based approaches. The Haar filter approach is further demonstrated to remain effective (100% detection, 0% false alarm, RMS estimation errors of <3%) at low SNRs of ∼0 dB.