Designing nonuniform linear arrays to maximize mutual information for bearing estimation.
Estimating the bearing of a narrowband sound source using a towed horizontal array is a common array processing problem. This paper designs nonuniform linear symmetric arrays of fixed apertures for estimating the bearing of a sound source. Specifically, the hydrophone spacings for a symmetric linear array are chosen to maximize the upper bound on the mutual information between the true bearing and the estimated bearing in spatially white noise. The arrays maximizing the mutual information while nulling the forward endfire direction look significantly different from the uniform arrays commonly used in towed systems. Arrays maximizing mutual information are helpful when bearing estimation is considered as a quantization problem to assign the source to the correct partition. The optimal partitions for the array are designed using the Lloyd algorithm with an inner product distortion metric based on maximizing the likelihood function of the observations. In these approaches, increasing the mutual information and optimizing the partitions should reduce the probability of error (P(e)) in choosing the partition containing an unknown source. Simulation results with MAP and ML estimators demonstrate that the optimum arrays and partitions proposed here have a much lower P(e) than the uniform array and uniform partitions.
Department of Electrical and Computer Engineering, University of Massachusetts Dartmouth, North Dartmouth, Massachusetts 02747-2300, USA.
Xiaoli
X
Zhu
John R
JR
Buck
D000162:Acoustics / Q000295:instrumentation*; D008962:Models, Theoretical; D009010:Monte Carlo Method; D009624:Noise, Transportation / Q000517:prevention & control*; D009792:Oceans and Seas; D012623:Seawater; D012767:Ships; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation*