Parameter Estimation in Array Processing

The paper deals with signal processing methods for the outputs of an array of sensors which sample a wavefield. The purpose of this signal processing is to obtain insight into the structures of the waves traversing the array. For example, location parameters of sources generating signals which are transmitted by the waves and spectral properties of these signals have to be measured. A typical application is sonar, where the sensors are hydrophones in the ocean and the signals are ship noise or echos. Signal processing in such sense is called array processing. Classical methods are known as beamforming which can be motivated, e.g. by spectrum estimation for wavefields. Limited apertures of the arrays result in limited resolution of beamforming. Then, location parameters of sources not well separated cannot be estimated by inspection of the beamformer output. Therefore, parametric statistical models and suitable parameter estimation methods have been developed. We review certain asymptotic distributional properties of the array output in the frequency domain and investigate maximum-likelihood estimates and corresponding numerical procedures. We also discuss possibilities for estimating the number of sources. We report of numerical experiments on the accuracy of simultaneous estimations of bearings, ranges and spectral powers of sources and compare with other high-resolution methods. The applicability of the methods to ultrasonic NDE is discussed.