JoEllen Wilbur

Underwater target detection using multichannel subband adaptive filtering and high-order correlation schemes

In this paper, new pre- and post-processing schemes are developed to process shallow-water sonar data to improve the accuracy of target detection. A multichannel subband adaptive filtering is applied to preprocess the data in order to isolate the potential target returns from the acoustic backscattered signals and improve the signal-to-reverberation ratio. This is done by estimating the time delays associated with the reflections in different subbands. The preprocessed results are then beamformed to generate an image for each ping of the sonar. The testing results on both the simulated and real data revealed the efficiency of this scheme in time-delay estimation and its capability in removing most of the competing reverberations and noise. To improve detection rate while significantly minimizing the incident of false detections, a high-order correlation (HOC) method for postprocessing the beamformed images is then developed. This method determines the consistency in occurrence of the target returns in several consecutive pings. The application of the HOC process to the real beamformed sonar data showed the ability of this method for removing the clutter and at the same time boosting the target returns in several consecutive pings. The algorithm is simple, fast, and easy to implement.

Nonlinear analysis of cyclically correlated spectral spreading in modulated signals

This paper examines the mapping from the Cohen class of bilinear time‐evolutionary spectral estimators (TES) to a conjoint frequency‐cycle frequency signal description for modulated acoustic signals. The transform mapping provides a cycle spectrum estimation that is used to identify cyclostationarity in modulated acoustic signals that often remains undetected in the one‐dimensional time history and power spectral density (PSD). The Wigner distribution (WD) TES is derived as the case for which the PSD used in stationary analysis of acoustic signals is preserved in the Fourier transform mapping to a conjoint frequency–frequency correlation signal representation for modulated signals. Fourier transformation over temporal window centers of a pseudo‐WD TES of modulated acoustic signals is shown to equate to the time‐variant cyclic spectrum, defined for cyclostationary signals, evaluated along the center of a moving average estimate. A pseudo‐WD TES based function mapping procedure for cycle frequency estimatio...

Isolation of Resonance in Acoustic Backscatter from Elastic Targets Using Adaptive Estimation Schemes

The problem of locating very low frequency sound sources in shallow water is made difficult by the interaction of propagating acoustic waves with the sea floor. It is known that low frequency sound waves enter the bottom and are converted to a variety of compressional and shear wave types, including seismic interface waves. One of the latter is the Scholte wave, which travels in an elliptical orbit along the sediment-water interface. Scholte waves, although dispersive, often have speeds very much slower than the speed of sound in water. Slow wave speeds and the attendant short wavelengths suggest that low frequency beamforming and source localization with sea floor geophones can be accomplished with relatively small arrays when compared with hydrophone arrays in the water column. To test the feasibility of this approach, experiments were carried out in the shallow water of the Malta Channel of the Straits of Sicily where the Scholte wave speed was some 10 to 20 times slower that the speed of sound in water. A linear array of ten vertically gimballed geophones was deployed and measurements were made on propagating seismic wave fields generated by explosive shots. The spatial coherence of the dispersive Scholle waves across the 40-m array was found to be above 0.9 for all shots, while the spatial coherence of the noise fell to 0.5 over a distance of 18 m along the array, indicating good prospects for array beamforming and noise rejection. Frequency dependent group velocities were obtained from the dataset and used to obtain phase velocities needed to implement an algorithm for dispersive beamforming. Since the phase velocities were quite low (130-200 m/s), narrow beams were formed at very low frequencies with this small array; half-power widths of 22° at 7 Hz and 16° at 11 Hz were obtained. The resulting directivities, beam patterns, and sidelobe characteristics are in excellent agreement with array theory, which suggests that coherent processing is a viable technique on which to base new applications for seismic arrays on the sea floor. Supporting material on the geophysics of Scholte waves is also presented, as are calculations of the wave field at the site, made possible by inversion of the velocity dispersion curves.The problem of underwater target detection and classification from acoustic backscatter is the central focus of this paper. It has been shown that at certain frequencies the acoustic backscatter from elastic targets exhibits certain resonance behavior which closely relates to the physical properties of the target such as dimeusion, thickness, and composition. Several techniques in both the time domain and frequency domain have been developed to characterize the resonance phenomena in acoustic backscatter from spherical or cylindrical thin shells. The purpose of this paper is to develop an automated approach for identifying the presence of resonance in the acoustic backscatter from an unknown target by isolating the resonance part from the specular contribution. An adaptive transversal filter structure is used to estimate the specular part of the backscatter and consequently the error signal would provide an estimate of the resonance part. An important aspect of this scheme lies in the fact that it does not require an underlying model for the elastic return. The adaptation rule is based upon fast Recursive Least Squares (RLS) learning. The approach taken in this paper is general in the sense that it can be applied to targets of unknown geometry and thickness and, further, does not require any a priori information about the target and/or the environment. Test results on acoustic data are presented which indicate the effectiveness of the proposed approach. V. CONCLUSION The paper proposed an on-line automatic measurement system which accurately measured the heaving, rolling, and pitching of ship by adequately processing the outputs of four accelerometers and one inclinometer appropriately located on the ship. By modeling the heaving, rolling, and pitching signals by adequate linear dynamic systems and using a bank of Kalman filters, on-line accurate measurement of ships attitude was realized. Further improvement of the accuracy of the measurement is achieved by increasing the number of the candidates used in a bank of Kalman filters.

A new time delay estimation in subbands for resolving multiple specular reflections

A new time delay estimation procedure is proposed using the multiresolution analysis framework through a discrete wavelet transform (DWT). Once the signals are decomposed, the time delays are estimated iteratively in each subband using two different adaptation mechanisms that minimize the mean squared error (MSE) between the reference and primary signals in the corresponding subband and level. The localization of the minima of the MSE curves at different levels and subbands is used in order to arrive at the time delay estimates. The proposed scheme is then applied to a real-life problem of underwater target detection from acoustic backscattered data.

Wigner/cycle spectrum analysis of spread spectrum and diversity transmissions

A high-resolution t- omega estimator, termed the Wigner distribution (WD), is shown to form a sound basis for representing nonstationary acoustic returns. Signal returns are modeled as the output of a time-variant random filter where the WD of the nonstationary signal return defines a random process whose expectation reduces to the instantaneous power spectral density defined for dispersive communication channels. From the WD, a set of relations describing time-variant channel effects on spread-spectrum and diversity transmissions are developed. These relations are shown to be useful in comparing spreading techniques under differing channel conditions and for estimating channel-imposed bounds on the spreading parameters required for effective transmission. A mapping from the Wigner distribution to the cycle spectrum is shown to produce cyclic correlations characteristic of the modulation rate. The WD-based formulation is applied to an example of spread-spectrum transmission through a reverberation-limited channel. >

Contourlet detection and feature extraction for automatic target recognition

This research presents a contourlet based detection and feature extraction method for underwater targets. The method operates on Side Scan Sonar (SSS) images and is designed to automatically detect and generate target features for classification. Kernel based classifiers are used to determine the best boundary for separating targets and clutter. A statistically significant target data set is generated by embedding additional synthetic targets into SSS data collected during sea tests. Feature trade off studies show an improvement in classification results with the addition of directional based features.

Channel characterization for communications in very shallow water

Broadband acoustic transmissions (7 kHz to 17 kHz) taken from July 4, 2000 to July 8, 2000, in the shallow water near Scripps Pier at La Jolla, California, are used to extract the time‐varying channel parameters of coherence time and multipath time delay spread, as functions of frequency and the environmental variables of wave height and tidal fluctuations. Tidal fluctuations, which have a significant effect on water depth at the receiver and transmitter, are shown to strongly correlate to variations in the multipath delay spread. Variations in the coherence time for the channel, as measured by the drop off in correlation between initial and successive impulse responses, are shown to be inversely related to variations in the measured wave height. The coherence time of the channel was found to decrease with increasing center frequency. A scatter plot of the receiver signal‐to‐noise ratio as a function of wave height and water depth indicates when the shallow water environment allows a viable communications...

Detection processing of complex beam-former output data: a new dispersion-based reconditioning algorithm

Detection processing of the Toroidal Volume Search Sonar beamformer output prior to image formation is used to increase the signal-to-reverberation. The energy detector and sliding matched filter perform adequately at close range but degrade considerably when the reverberation begins to dominate. The skewness matched filter offers some improvement. A dispersion based reconditioning algorithm, introduced in this paper, is shown to provide considerably improvement in the signal-to-reverberation at far range.

Post processing of sonar imagery using recursive high order correlation method

In processing of sonar data, beamforming process plays a central role in reducing the effects of the surface and bottom reverberation. In shallow water environments where the reverberation is dominant, target detection from the beamformed results is not effective and may lead to significantly high false alarm rate. This paper presents a novel approach for post processing sonar beamformed imagery in order to improve the detectability of the targets while substantially reducing the occurrence of the false detection. This is done using the recursive high order correlation (RHOC) method which exploits the spatial-temporal correlation between consecutive pings of the beamformed images. Test results on several sets of sonar data show the great efficiency and power of the proposed method especially in very high cluttered environments.

Target detection from TVSS shallow-water data using a multichannel subband adaptive filtering scheme

In processing the Toroidal Volume Search Sonar (TVSS) data, the primary challenge is to detect targets in highly reverberant environments. This may be done by processing each sonar channel separately and estimating the time delays associated with the specular returns and then isolating these components from the background noise prior to beamforming. However, if there is significant reverberation it is difficult to accurately estimate time delays using only one sonar channel. Therefore, a multi-channel method is introduced that exploits the interdependency of adjacent sonar stave data. The method starts by enhancing signal to noise by combining multiple stave data after suitable phase compensation for array geometry. Next, time delays of the specular returns are estimated from the discrete wavelet sub-bands of the combined signal using a least squares method. The new method has been tested on several TVSS data sets, and the results are promising for even the most reverberant cases.