Model-based processing for a large aperture array

A model-based approach to solve a deep water ocean acoustic signal processing problem based on a state-space representation of the normal-mode propagation model is developed. The design of a model-based processor (MBP) for signal enhancement employing an array consisting of a large number of sensors for a deep ocean surveillance operation is discussed. The processor provides enhanced estimates of the measured pressure-field, modes, and residual (innovations) sequence indicating the performance or adequacy of the propagation model relative to the data. It is shown that due to the structure of the normal-mode model the state-space propagator is not only feasible for this large scale problem, but in fact, can be implemented by a set of decoupled parallel second-order processors, implying a real-time capability. In the paper we discuss the design and application of the processor to a realistic set of simulated pressure-field data developed from a set of experiments and sound speed parameters     

Modified Pairwise Spectrogram Processing for Localization of Unknown Broadband Sources

Pairwise waveform (PWW) and pairwise spectrogram (PWS) processors for 3-D localization of unknown, continuous-wave, broadband sources in shallow water have been developed and implemented. The processors use sparse hydrophone arrays and are applicable to multiple sources, which can be unknown, continuous wave, and broadband. Here, we give new formulas for these two processors that significantly reduce computational requirements, making localization at longer ranges and higher frequencies feasible. The new processors are motivated by a demonstration that an incoherent version of the PWW (IPWW) processor (in which processor outputs at different frequencies are averaged after being processed independently) is the Bartlett processor without autoreceiver terms. The new PWW processor is mathematically equivalent to the original version, though much faster. The new PWS processor is mathematically equivalent to the original version only in the limit of infinite spectrogram window length, but for window lengths that are optimal with the old PWS processor, the new PWS processor gives essentially the same results with much greater speed. Simulations comparing PWS processing to Bartlett, PWW processing, and a time difference of arrival method indicate that the main advantage of PWS processing is for multiple sources in uncertain, high-noise environments at ranges many wavelengths long. With PWS, increased robustness with respect to mismatch is obtained at the expense of reduced resolution; varying PWS processor parameters (such as the size of windows used to create spectrograms) optimizes this tradeoff. This work is motivated by the problem of localizing singing humpback whales, and simulation results use whale sources.     

Adaptive beamforming: spatial filter designed blocking matrix

Controlling the resolution in adaptive beamformers is often crucial. A simple method that works for both narrow-band and broad-band arrays is presented. This method is based on the normalized leaky LMS algorithm in conjunction with a generalized sidelobe canceller (GSC) structure, where the GSC is designed using a spatial filtering approach. In essence, the suppression of the spatial filters and the implicit noise of the leaky LMS algorithm together determine the adaptive beamformer. Analytical expressions are given for the Wiener filters and the output spectrum versus frequency and point source location. These expressions are employed in the design specification of the spatial filters and to obtain conditions for a controlled quiescent beamformer response. Simulation results are presented to illustrate the behavior of the array     

The TAP III beamforming system

The Three-Array Processor (TAP III) beamforming system incorporating both wide-band time-domain beamforming and narrow-band frequency-domain beamforming is described. This paper briefly develops the beamforming theory and shows how the fast Fourier transform (FFT) is applied to accomplish frequency-domain beamforming. The frequency-domain beamformer operates in the frequency domain to form beams and power spectrum data over narrow frequency bands of interest. A real-time digital filtering technique is used to extract the narrow bands of interest from the broad-band input signal. The frequency-domain beamformer accomplishes real-time digital filtering and beamforming by using a high-speed array processor to do the complex calculations and data handling required by the algorithm. The time-domain beamformer operates in parallel with the frequency-domain beamformer to form up to 16 broad-band beams in the time domain. A programmable all-pass digital filter is used to create the fine time delays required by the time-domain beamformer.     

The effect of phase-shifter errors on the performance of an antenna-array beamformer

The paper considers the random phase errors in the phase shifters which are used in an antenna array to steer the beam in the look direction, and analyzes the effect of these errors on the performance of the optimal processor which maximizes the output SNR by deriving the expressions for the output signal power, residual interference power, output SNR, and the array gain as a function of the variance of these errors. The paper also considers the phase quantization error which arises in the digital phase shifters and shows how the performance of the optimal processor depends on the number of bits of the digital phase shifters.     

A posteriori probability source localization with uncertainmesoscale eddy currents

Long-range source localization is shown to be affected by a mesoscale eddy whose realization is solely a cyclonic current (no thermal manifestation). The sensitivity of a matched-field type processor (known ocean) to an eddy is demonstrated, as well as its sensitivity to a mismatch between the parameters of the eddy and the processor assumptions. Optimum uncertain field processing techniques are used to overcome these sensitivities by incorporating uncertainties about the environment into the processor. These processors operate on data produced by a special 3-D ray tracer using actual sound speed data and two different models for eddy current structure     

Programmable switched-capacitor neural network for MVDR beamforming

In this paper, a real-time adaptive antenna array based on a neural network approach is presented. Since an array operating in a nonstationary environment requires a programmable synaptic weight matrix for the neural network, the switched-capacitor (SC) circuits with the capability of programmability and reconfigurability is conducted to implement the neural-based adaptive array. Moreover, the SC techniques can directly implement the neural network with less chip area and provide the ratio of SC-equivalent resistors with accuracy of 0.1 percent. Programming of the switched-capacitor values could be made by allocating each synaptic weight to a set of parallel capacitors with values in a digitally programmable capacitor array (PCA). A relatively wide range of values (5 to 10 binary bits resolution) can be realized for each synaptic weight. A simulation tool called SWITCAP is used to verify the validity and performance of the proposed implementation. Experimental results show that the computation time of solving a linear array of 5 elements is about 0.1 ns for 1 ns time constant and is independent of signal power levels     

The AWSUM filter: a 20-dB gain fluctuation-based processor

The advanced WISPR summation (AWSUM) filter, a natural extension of the WISPR filter for higher filter order numbers, is presented and its performance is compared to the performance of the WISPR filter and the conventional summation processor. It is shown that the AWSUM filter achieves substantial gains in various measures of processor performance above those of the other two processors in spatial and spectral resolution, minimum detectable level (MDL), clutter reduction, and signal-to-noise ratio (SNR) gain. The important processing parameters are shown to be the percentage of overlap of the voltage time series and the number of FFT's averaged. SNR gains in excess of 20 dB were shown to be achievable for low-fluctuation amplitude tonals using measured data     

Broad-band geoacoustic inversion in shallow water from waveguideimpulse response measurements on a single hydrophone: theory andexperimental results

The paper discusses an inversion method that allows the rapid determination of in situ geoacoustic properties of the ocean bottom without resorting to large acoustic receiving apertures, synthetic or real. The method is based on broad-band waterborne measurements and modeling of the waveguide impulse response between a controlled source and a single hydrophone. Results from Yellow Shark '94 experiments in Mediterranean shallow waters using single elements of a vertical array are reviewed, inversion of the bottom parameters is performed with an objective function that includes the processing gain of a model-based matched filter (MBMF) receiver relative to the conventional matched filter. The MBMF reference signals incorporate waveguide Green's functions for known geometry and water column acoustic model and hypothesized bottom geoacoustic models. The experimental inversion results demonstrated that, even for complex environmental conditions, a single transmission of a broad-band (200-800 Hz) coded signal received at a single depth and a few hundred forward modeling runs were sufficient to correctly resolve the bottom features. These included the sound speed profile, attenuation, density, and thickness of the top clay sediment layer, and sound speed and attenuation of the silty clay bottom. Exhaustive parameter search proved unequivocally the low-ambiguity and high-resolution properties of the MBMF-derived objective. The single-hydrophone results compare well with those obtained under identical conditions from matched-field processing of multitone pressure fields sampled on the vertical array. Both of these results agree with expectations from geophysical ground truth. The MBMF has been applied successfully to a field of advanced drifting acoustic buoys on the Western Sicilian shelf, demonstrating the general applicability of the inversion method presented     

Spatio-temporal processing of coherent acoustic communication datain shallow water

Achieving reliable underwater communication in shallow water is a difficult task because of the random time-varying nature of multipath propagation. When the product of Doppler-related signal bandwidth spread and multipath-related time spread of the channel is larger than one, some types of adaptive signal processing may not work very well. In this paper, various methods of coherent space-time processing are compared for a condition of a marginally overspread channel operating at 50 kHz. Various combinations of suboptimal spatially adaptive and time adaptive methods are considered. The coherent path beamformer (CPB) and recursive least squares (RLS) adaptive beamformer, both in combination with RLS time filtering, are analyzed. Also considered in the analysis is the combined RLS space-time optimal adaptive processor. Many experiments using broad-band phase-shift-keyed transmissions in shallow water have been conducted to provide data for testing these various processing methods. Because of the rapid time variation of the multipath, the product of bandwidth spread and time spread at this test site approached unity. In this environment, a suboptimal approach consisting of the adaptive beamformer followed by RLS equalization reduced reverberation and transmission errors     

Interpretation of frequency-dependent transmission-lossinterference patterns

Experimental observations of broad-band acoustic propagation in a known geological region of the Atlantic Generating Station (AGS) site (1994) has prompted a new approach to understanding frequency-dependent behavior in shallow-water regions. A modal-based theory is presented to explain quantitatively the interference patterns of transmission loss versus frequency observed in the experimental data. It is shown that the higher modes are responsible for observed interference patterns and that these can be related to modal group velocities using an ideal waveguide model. This may provide new insights applicable to existing inverse techniques     

Synthesis of symmetric flattop radiation patterns

In this communication, the design of ring arrays that produce symmetric flattop radiation patterns with low sidelobes is presented. The equivalent linear array approach is used in the design of the array. A newly developed iterative algorithm is employed to obtain a prototype linear array that generates a desired flattop pattern. A new concept of common scale factor of ring arrays is introduced, which not only adds flexibility to the design, but also reduces the complexity of the array. In the design examples presented, it is shown that an almost flattop pattern with maximum ripple less than 0.075 dB and sidelobe levels less than 28 dB can be achieved using only 10 ring radiators     

Geoacoustic inversion of range-dependent data with added Gaussian noise

A rotated coordinates inversion algorithm is used on subsets of the Inversion Techniques 2001 Geoacoustic Workshop data, to which white Gaussian noise is added. The resulting data sets are equivalent to noisy broad-band signals received on a horizontal line array (HLA) during a single integration time interval. The inversions are performed using a technique called systematic decoupling using rotated coordinates (SDRC), which expands the original idea of rotated coordinates by using multiple sets of rotated coordinates, each corresponding to a different set of bounds, to systematically decouple the unknowns in a series of efficient simulated annealing inversions. The cost function minimized in the inversion is based on the coherent broad-band correlation between data and model cross spectra, which increases the coherence gain of the signal relative to incoherent noise. Using the coherent broad-band cost function with sparse HLA-like data sets, the SDRC inversion method yields good estimates for the sensitive environmental parameters for signal-to-noise ratios as low as -15 dB.     

Tomographic mapping of sediments in shallow water

Sediment compressional wave speeds were estimated using broad-band data in range-dependent environments. The environment was assumed as mildly range dependent and was modeled using adiabatic theory. The inversion scheme was based on group speed-dispersion behavior. A genetic algorithm (GA) combined with a neighborhood approach was used for the search. The top layer of sediment was mapped in the shelf region using acoustic data from explosive sources collected on a vertical line array.     

Matched-field processing for broad-band source localization

In the Hudson Canyon experiment, a sound source moved at a constant depth in 73 m of water while transmitting four tonals. The signal was received on a vertical array of hydrophones that spanned the water column. The data set from this experiment has become a standard test case for studying source tracking using matched field processing. As part of that process it was important to first determine a suitable environment model and demonstrate the feasibility of matched-field processing. In this paper, we provide the background on the original data processing that was done to accomplish this. Several interesting results emerged from that study. Frequency averaging was demonstrated to be extremely beneficial when used with the Bartlett processor. However, the popular Minimum Variance processor performed poorly. Finally we discuss a very simple approach to combining the energy coherently that provided significantly improved results.     

Modal time-series structure in a shallow-water environment [HudsonCanyon region]

The broad-band acoustic characterization of the Hudson Canyon region off the New Jersey Continental Shelf is studied with an analysis of pressure time series generated by small explosive sources and recorded on a vertical line array (VLA). The average water depth is about 72 m and the average sound-speed profile (SSP) is downward-refracting over the midportions of the water column. The seabed is characterized by sediment layers possessing sand-like characteristics. The sound-speed structure of the water column and the seabed structure create distinguishing modal features in the impulse response in the 250-500-Hz hand. The details of the depth and range dependence of the time series on the VLA are sensitive to small perturbations of the structure of the upper layer of the SSP, the water depth, and the seabed structure. This sensitivity of the acoustic field is investigated using a broad-band range-dependent normal mode model called NAUTILUS. The representation of the spatial and temporal structure of the time series in terms of a modal structure reveals several unique effects of the SSP and the geoacoustic structure of the bottom on the group velocity of the modes over a large bandwidth. Individual modes can be identified in the measured data using direct data-simulation comparisons. Cross-correlation values between data and simulations in a 155-ms time window generally vary from 0.7 to 0.9 for sensors below the thermocline but are much smaller for sensors above the thermocline     

On Performance of Array Signal Processing

A unified treatment for performance evaluation of various array signal processors is presented. Detection performance is expressed in terms of the parameter of the power-type receiver operating characteristic (ROC) for optimum, beamformer, and null-steerer detectors. Estimation performance is analyzed in terms of the normalized mean-square error (MSE) for minimum mean-square error (MMSE) and maximum likelihood estimators (MLE's) under a varying noise environment. Sensitivity of the detection/estimation performance to the varying internal and directional noise sources is investigated. An interesting inverse relationship is presented between the normalized MSE of the MMSE estimator and the power-type ROC parameter for the optimum detector.     

Adaptive separation of mixed broadband sound sources with delays bya beamforming Herault-Jutten network

The Herault-Jutten network has been used to separate independent sound sources that have been linearly mixed. The problem of separating a mixture of several independent signals in free-field conditions or a signal and echoes in confined spaces is compounded by propagation time delays between the source(s) and the microphones because the conventional Herault-Jutten network cannot tolerate time delays. In this paper, we combine a symmetrically balanced beamforming array with the conventional Herault-Jutten network. The resulting system can adaptively separate signals that include delays introduced by the propagation medium. The proposed algorithm has been simulated in digital communication multipath channels where intersymbol interference exists. The simulation results show two clear advantages of the proposed method over the conventional adaptive equalization: (1) there is no penalty for very long impulse responses caused by long delays, and (2) no training signals are needed for equalization. The design of a multibeamformer to handle the source separation of multiple broad-band signals is also presented     

Spatial smoothing and minimum variance beamforming on data fromlarge aperture vertical line arrays

Various approaches to the beamforming of data from large aperture vertical line arrays are investigated. Attention is focused on the conventional beamforming problem where the angular power spectrum is estimated, in this case by the adaptive minimum variance processor. The data to be processed are 200 Hz CW transmissions collected at sea by a 900 m vertical line array with 120 equally spaced sensors. Correlated multipath arrivals result in signal cancellation for the adaptive processor, and spatial smoothing techniques must be used prior to beamforming. The processing of subapertures is proposed. Full aperture and subaperture processing techniques are used on the 200 Hz data. Multipath arrivals are found to illuminate only parts of the array, thus indicating that the wavefield can be highly inhomogeneous with depth     

Experimental matched-field localization results using a short vertical array and mid-frequency signals in shallow water

Traditionally, matched-field processing (MFP) has been used to localize low-frequency sources (e.g., <300 Hz) from their acoustic signals received on long vertical arrays. However, some sources emit acoustic signals of much higher frequency. Applying MFP to signals in the mid-frequency range (e.g., 1-4 kHz) is a very challenging problem because MFP's sensitivity to environmental parameter mismatch becomes more severe with increasing frequency. Robust MFP techniques are required to process signals in the mid-frequency range. As a practical issue, short vertical arrays are more convenient to work with than are long vertical arrays; they are easier to deploy and are less prone to large amounts of deformation. However, short vertical arrays undersample the water column, which can result in severely degraded MFP performance. In this paper, we present experimental data results for this nonconventional paradigm. Using the environmentally robust broad-band L/sub /spl infin//-norm estimator, MFP results are given using shallow-water experimental data. This data consisted of broad-band signals in the 3-4-kHz band collected on an eight-element 2.13-m vertical array. These results serve to demonstrate that good localization performance can be attained for this difficult problem. Guidelines on the appropriate use of ray and normal-mode propagation models are also presented.