A fixed cw source in the Central Arctic was accurately localized in range and depth using wave-based full-field ambiguity function techniques. The data were taken during the Fram IV experiment, utilizing a vertical array spanning the upper 960 m of a deep-water environment (generally greater than 2800 m) and a high SNR signal from a 20-Hz source at a distance of 270 km from the array, both suspended from the ice cover. The predicted field was computed using a fast field program. Both a linear correlation of the predicted field with the received field and a maximum likelihood method (MLM) estimator correctly localized the source. The MLM estimator produced sidelobes significantly below the main peak, while the linear correlator produced sidelobes sufficiently large to be taken as false targets. The linear processor, however, was less sensitive to mismatch between the predicted and measured field. Array gain for the linear estimator was found to be 2 dB higher than for a conventional plane-wave beamformer.
Matched-field processing is a signal processing technique for arrays in which field vectors for assumed source positions (range and depth) are substituted for plane-wave steering vectors in conventional linear and nonlinear beamformers. The field vectors are computed by standard acoustic field models (FFP, normal mode, etc.) which take into account propagation effects in an oceanic waveguide. The output is an ambiguity surface over possible source positions in which a peak is expected at the true source position. Accuracy of the computed fields is limited in large part by our knowledge of the environment. This environmental mismatch causes degradation in localization performance, sometimes leading to large errors in estimation of source position. In order to assess the significance of this effect, simulations were performed in which a measured field is synthesized using a slightly different environmental model from that used for the steering vectors. The differences were introduced to simulate expected errors in sound-speed profile, sediment thickness, and elastic wave speed. Calculations were made for a cw source operating at 10 Hz and depths of 25 and 250 m in a 500 m-deep ocean. The receiver was a 16-element vertical array at ranges of 25 (shadow zone) and 100 km (second convergence zone). A typical Pacific sound velocity profile was assumed. The bottom was modeled by a thin (50-m) sediment layer overlying an elastic subbottom. Degradation in localization performance due to environmental mismatch will be discussed both quantitatively and qualitatively.
For many acoustic environments a target's acoustic field incident on a hydrophone array segment is not representable by a plane wave, but is a function, generally, of three coordinates: range, depth, and bearing. In these cases a conventional beamformer, which is designed to detect plane waves, cannot localize the target accurately. Techniques have been developed recently to exploit the complexity of the field to estimate the source location coordinates by correlating the received field on the array with accurate replicas of the acoustic field, derived from knowledge of the environment. The potential utility of such techniques has been demonstrated in determining range and depth for simulated high-SNR signals. In this paper, however, they are shown to exhibit excessive sidelobes for low SNR. To alleviate this problem, two high-resolution techniques, the Maximum Likelihood Method (MLM I and “Alternate Orthogonal Projection” (AOP), or linear predictor, are applied to the simulated case of one target in white noise in a Pekeris environment. MLM is seen to produce stable main peaks which localize targets precisely with low sidelobes, while AOP is shown to be unstable in the presence of random noise and to produce false peaks even when the noise fields are stable.
For many environments, a target’s acoustic field incident on a hydrophone array segment is not representable by a plane wave, but is a function, generally, of three coordinates: range, depth, and bearing. This complexity in the received field causes a conventional plane-wave beamformer to suffer a degradation in its performance. Techniques have been developed recently to exploit the complexity of the field to estimate the source location coordinates by correlating the received field on the array with accurate replicas of the acoustic field, derived from knowledge of the environment. The potential utility of such techniques has been demonstrated in determining range and depth; however, they can exhibit excessive sidelobes for low-SNR sources. To alleviate this problem, two high-resolution techniques, the maximum likelihood method (MLM) and ‘‘approximate orthogonal projection’’ (AOP), or linear predictor, are applied to the simulated case of one target in white noise in a Pekeris environment. The MLM is seen to produce stable main peaks that localize targets precisely with low sidelobes, while AOP is shown to be unstable in the presence of random noise and to produce false peaks even when the noise fields are stable.
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