Wideband Array Signal Processing Using Sequential Monte Carlo Methods

This paper proposes a novel online tracking, waveform recovery, and detection algorithm for wideband array signal processing. The proposed method extends the wideband data model developed in [1] to the online case through use of particle filters. This proposed method finds application in various areas of telecommunications, including radar, sonar, and other wireless communication problems, where locating moving targets and extracting the waveforms for classification are needed. The proposed method first detects the number of unknown wideband sources using a hypothesis testing procedure, followed by the sequential estimation of the DOAs of these identified sources, and the extraction of the waveform of these sources, using a particle filter. Computer simulations demonstrate the ability of the proposed method to detect the time-varying number of sources in different scenarios as time progresses. The results also show that the DOA trajectories of the identified sources are well tracked and their signal waveforms are also well restored. Finally, the posterior Cramér-Rao bound (PCRB) [2] is also presented to demonstrate that the estimates by the proposed method lie consistently within the bound.