A performance analysis of two linear array processing algorithms for obstacle localization
Proceedings of SPIE - The International Society for Optical Engineering
533 - 544
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The performance of a commonly employed linear array of sonar sensors is assessed for point- target localization. Two different methods of combining time-of-flight information from the sensors are described to estimate the range and azimuth of the target: pairwise estimate method and the maximum likelihood estimator. The biases and variances of the methods are investigated and their combined effect is compared to the Cramer-Rao Lower Bound. Simulation studies indicate that in estimating range, both methods perform comparably; in estimating azimuth, maximum likelihood estimate is superior at a cost of extra computation.
Maximum Likelihood Estimate
Cramér-Rao Lower Bound