Volume 115, Issue 3, March 2004
Index of content:
- ACOUSTIC SIGNAL PROCESSING 
115(2004); http://dx.doi.org/10.1121/1.1643363View Description Hide Description
Identification algorithms are considered for a class of targets situated near the bottom of a water channel. It is assumed that the target-sensor distance relative to the channel depth is such that a ray-based representation of the scattered fields is appropriate (vis-à-vis a modal representation). Two approaches are considered for processing the scattered fields. In one algorithm a deconvolution is performed to remove the channel response, and thereby recover the free-field target scattered signature. In this case the classifier is trained based on free-field data. In the second approach the array receiver is employed to point the sensor in particular directions, and the beam-formed signal is used directly in the subsequent classifier. In this case the classifier must be trained based on in-channel data. Multiple scattered signals are measured, from a sequence of target-sensor orientations, with the waveforms classified via a hidden Markov model. Example results are presented for scattering data simulated via the finite-element method and coupled to a normal-mode waveguide modal, for elastic targets situated in a water channel.
115(2004); http://dx.doi.org/10.1121/1.1647491View Description Hide Description
The problem considered here is that of tracking a single underwater target in clutter using multilateral time-delay measurements derived from short-duration acoustic emissions, or transients, radiated by the target. The target is moving linearly with constant velocity and depth. To account for the effects on the time-delay estimates due to acoustic propagation in uncertain environments, the time-delay measurement errors between pairs of sensors are modeled using Gaussian mixture distributions. An approach is proposed that utilizes an iterative maximum likelihood optimization technique based on the expectation-maximization algorithm. In each iteration a nonlinear least-squares procedure is used to compute the target model parameters. A detection mechanism is also formulated that can validate the correctness of the estimated track parameters and verify the existence of a target. The proposed method is tested using simulated time-delay measurements from a linear array of three equally spaced sensors mounted onboard an observer platform. Extensive tests are performed for several scenarios with different tracking geometry.