Abstract
A pulse Doppler radar worked in medium or high pulse repetition frequency (PRF) may suffer from range and Doppler ambiguities. The common method to solve ambiguities is to use multiple PRFs and do correlation between them. The ghosting problem may be caused by the false alarms in the correlation. When the signal-to-noise ratio is low, a low detection threshold is needed to guarantee the probability of detection, which may create a large amount of false alarms that are intractable for existing techniques. This study uses a Bayesian method to detect and track a single target in a range and Doppler ambiguous radar. The authors’ method is formulated based on the finite set representation of the target state and the recently developed Bernoulli filter. Besides, a sequential Monte Carlo implementation of the Bernoulli filter is proposed for the problem of range and Doppler ambiguous measurement. Simulation results show that the proposed filter can simultaneously detect and track the target using the ambiguous measurements in the presence of dense false alarms.
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