DIET AWSUM: a fluctuation-based deconvolution technique forenhancing signal-to-noise ratio and resolution

A technique for simultaneously improving resolution and signal-to-noise ratio gain, the directivity improved estimation technique (DIET) combined with the advanced WISPR summation (AWSUM), or DIET AWSUM, is introduced. The DIET AWSUM method combines a straightforward deconvolution technique with the highly fluctuation-sensitive AWSUM filter. DIET AWSUM results generated for ocean acoustic data are compared with estimates produced using the maximum entropy method (MEM), a well-tested standard. The DIET AWSUM method achieved superior results in both increased resolution and improved gain for stable signal identification chiefly because of its greater ability to discriminate between stable signals and fluctuating signals and noise     

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 Study of Spatial Processing Gain in Underwater Acoustic Communications

Spatial processing, including beamforming and diversity combining, is widely used in communications to mitigate intersymbol interference (ISI) and signal fading caused by multipath propagation. Beamforming suppresses ISI (and noise) by eliminating multipath (and noise) arrivals outside the signal beam. Beamforming requires the signals to be highly coherent between the receivers. Diversity combining combats ISI as well as signal fading by taking advantage of the independent information in the signal. Classical (spatial) diversity requires that signals are independently fading, hence are (spatially) uncorrelated with each other. In the real world, the received signals are neither totally coherent nor totally uncorrelated. The available diversity is complex and not well understood. In this paper, we study the spatial processing gain (SPG) as a function of the number of receivers used, receiver separation, and array aperture based on experimental data, using beamforming and multichannel combining algorithms. We find that the output symbol signal-to-noise ratio (SNR) for a multichannel equalizer is predominantly determined by the array aperture divided by the signal coherence length, with a negligible dependence on the number of receivers used. For a given number of receivers, an optimal output symbol SNR (OSNR) is achieved by spacing the receivers equal to or greater than the signal coherence length. We model the SPG in decibels as the sum of the noise suppression gain (NSG, equivalent to signal-to-noise enhancement) and the ISI suppression gain (ISG, equivalent to signal-to-ISI enhancement) both expressed in decibels; the latter exploits the spatial diversity and forms the basis for the diversity gain. Data are interpreted using the modeled result as a guide. We discuss a beam-domain processor for sonar arrays, which yields an improved performance at low-input SNR compared to the element-domain processor because of the SNR enhancement from beamforming many sensors.     

Optimal tonal detectors based on the power spectrum

The detection of tonals embedded in noise is an important sonar function and the traditional power spectrum analysis method has been widely used for this purpose. Wagstaff et al. (1997) proposed the WISPR (Wagstaff's Integration Silencing PRocessor) family processors, which perform a nonlinear integration or combination of the power spectrum observations. In this paper, we analyze the statistical property of the power spectrum observations and develop novel tonal detectors by optimally integrating the spectrum observations. The optimal detectors are derived by using the method of maximum likelihood hypothesis test. The results from simulations and real sea trial data have shown that the proposed detectors are promising in detecting tonals     

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     

Active sonar detection in shallow water using the Page test

The use of active sonar in shallow water results in received echoes that may be considerably spread in time compared to the resolution of the transmitted waveform. The duration and structure of the spreading and the time of occurrence of the received echo are unknown without accurate knowledge of the environment and a priori information on the location and reflection properties of the target. A sequential detector based on the Page test is proposed for the detection of time-spread active sonar echoes. The detector also provides estimates of the starting and stopping times of the received echo. This signal segmentation is crucial to allow further processing such as more accurate range and bearing localization, depth localization, or classification. The detector is designed to exploit the time spreading of the received echo and is tuned as a function of range to the expected signal-to-noise ratio (SNR) as determined by the transmitted signal power, transmission loss, approximate target strength, and the estimated noise background level. The theoretical false alarm and detection performance of the proposed detector, the standard Page test, and the conventional thresholded matched filter detector are compared as a function of range, echo duration, SNR, and the mismatch between the actual and assumed SNR. The proposed detector and the standard Page test are seen to perform better than the conventional thresholded matched filter detector as soon as the received echo is minimally spread in time. The use of the proposed detector and the standard Page test in active sonar is illustrated with reverberation data containing target-like echoes from geological features, where it was seen that the proposed detector was able to suppress reverberation generated false alarms that were detected by the standard Page test     

Differences between passive-phase conjugation and decision-feedback equalizer for underwater acoustic communications

Passive-phase conjugation (PPC) uses passive time reversal to remove intersymbol interferences (ISIs) for acoustic communications in a multipath environment. It is based on the theory of signal propagation in a waveguide, which says that the Green's function (or the impulse-response function) convolved with its time-reversed conjugate, summed over a (large-aperture) vertical array of receivers (denoted as the Q function) is approximately a delta function in space and time. A decision feedback equalizer (DFE) uses a nonlinear filter to remove ISI based on the minimum mean-square errors (mmse) between the estimated symbols and the true (or decision) symbols. These two approaches are motivated by different principles. In this paper, we analyze both using a common framework. We note the commonality and differences, and pros and cons, between the two methods and compare their performance in realistic ocean environments, using simulated and at-sea data. The performance measures are mean-square error (mse), output signal-to-noise ratio (SNR), and bit-error rate (BER) as a function of the number of receivers. For a small number of receivers, the DFE outperforms PPC in all measures. The reason for poor PPC performance is that, for a small number of receivers, the Q function has nonnegligible sidelobes, resulting in nonzero ISI. As the number of receivers increases, the BER for both processors approaches zero, but at a different rate. The modeled performance differences (in mse and SNR) between PPC and DFE are in general agreement with the measured values from at-sea data, providing a basis for performance prediction.     

Performance Analysis for Matched-Field Source Localization: Simulations and Experimental Results

Matched-field methods concern estimation of source locations and/or ocean environmental parameters by exploiting full wave modeling of acoustic waveguide propagation. Typical estimation performance demonstrates two fundamental limitations. First, sidelobe ambiguities dominate the estimation at low signal-to-noise ratio (SNR), leading to a threshold performance behavior. Second, most matched-field algorithms show a strong sensitivity to environmental/system mismatch, introducing biased estimates at high SNR. In this paper, some theoretical developments on matched-field performance analysis are summarized, including Bayesian performance bounds and probabilistic ambiguity analysis, both incorporating environmental/system uncertainty/mismatch. Performance analysis is then implemented for source localization in a typical shallow water environment chosen from the Shallow Water Evaluation Cell Experiments (SWellEX). The performance predictions describe the simulations of the maximum-likelihood estimator (MLE) well, including the mean-square error (MSE) in all SNR regions as well as the bias at high SNR. The threshold SNR and bias predictions are also validated through SWellEX experimental data processing. The results suggest the current environmental, acoustic, and statistical modeling has developed to such a level that the optimum theoretical matched-field performance can be achieved in a well-controlled experiment.     

Signal processing for precise ocean mapping

In this work a bottom return signal model and accompanying signal processor are described for a wide swath bottom mapping system. An incoherent scattering model is employed under the assumptions that the bottom is a random rough surface composed of a large number of independent scatters with spatial correlation distance negligible relative to the ensonified area. The envelope of the signal received from the various spatial directions is modeled as a smooth, nearly Gaussian-shaped function representing the effects of the twoway spatial beam pattern, angle of incidence, and depth corrupted by multiplicative and additive noise stochastic processes. A signal processor is derived which makes use of the a priori information vested in this smooth function to provide a matched filter for the received signal envelope for each spatial direction. Computer simulation results are presented and the performance of the signal processor examined in a qualitative fashion.     

Adaptive pulselength correction (APLECORR): a strategy for waveformoptimization in ultrawideband active sonar

This paper describes adaptive pulselength correction (APLECORR), an environmentally adaptive technique for optimizing the detection performance in wide-band active sonars in so-called doubly spread channels. It works by allocating available transmit energy to frequency bands according to the in situ measured reverberation and ambient noise spectra. It optimizes the waveform and the detection processor at the same time. It is appealing in its simplicity and achieves significant gains whenever the reverberation-to-noise ratio is not constant across frequency, thus its applicability to wide-band systems. The method extends easily to PRN and other non-FM waveforms. The paper includes a proof that time spreading and frequency-spreading distortion have an approximately equivalent effect if the waveform is linear or hyperbolic frequency modulation     

Harbor surveillance radar detection performance

System requirements for harbor surveillance radars are reviewed. Experimental sea clutter data are presented and shown to be closely matched by a log-normal clutter model. Characteristics and parameters of the log-normal clutter model are described. Detection performance against a steady target in a log-normal clutter background, using logarithmic receivers, is provided. A log-normal target model is described. Detection curves for log-normal fluctuating targets in log-normal clutter are developed. A Constant False Alarm Rate (CFAR) processor that adaptively functions in log-normal clutter is described. CFAR detection performance is derived and presented in the form of CFAR loss curves.     

Acoustic model-based matched filter processing for fadingtime-dispersive ocean channels: theory and experiment

It is shown that the performance of a conventional matched filter can be improved if the reference (replica) channel compensates for the distortion by the ocean medium. A model-based matched filter is generated by correlating the received signal with a reference channel that consists of the transmitted signal convolved with the impulse response of the medium. The channel impulse responses are predicted with a broadband propagation model using in situ sound speed measured data and archival bottom loss data. The relative performance of conventional and model-based matched filter processing is compared for large time-bandwidth-product linear-frequency-modulated signals propagating in a dispersive waveguide. From ducted propagation measurements conducted in an area west of Sardinia, the model-based matched filter localizes the depths of both the source and receiving array and the range between them. The peak signal-to-noise ratio for the model-based matched filter is always larger than that of the conventional filter     

Passive sonar detection and localization by matched velocityfiltering

This paper presents a new bearings-only method of detecting and tracking low signal-to-noise ratio (SNR) wideband targets on a constant course and velocity trajectory. A track-before-detect strategy based on matched velocity filtering is adopted using spatial images constructed from a sequence of power bearing map (PBM) estimates accumulated during a track. To lower the threshold SNR for detection, a discrete bank of matched velocity filters integrates the PBM images over a range of hypothesized trajectories, such an approach eliminates the need to estimate the number of targets since signal detection is determined by comparing the output of each matched filter (MF) to a decision threshold. The distribution of the MF output is derived based on a single point target in diffuse noise assumption. Receiver operating characteristic curves show a definite detection gain under low SNR conditions for matched velocity filtering (track-before-detect) over detection from a single PBM     

Performance analysis of the incoherent and skewness matched filterdetectors in multipath environments

For cases in which a received signal is known exactly and the additive noise is white and Gaussian, the optimal detector can be implemented as a matched filter followed by a threshold comparator. However, the performance of this detector is sensitive to signal shifts and mismatch between the assumed and the actual structure of the received signal. As such, the use of a matched filter detector in a multipath environment can result in substantially poorer performance than expected. Here, it is shown that the use of the incoherent (or sliding) matched filter can also result in a substantial performance loss if the signal autocorrelation function is narrow relative to the interarrival times of the pulses. In contrast, a detector that compares the zero-zero lag of the matched filter cumulant sequence to a threshold has a performance that is relatively insensitive to multipath channels     

Robust broadband matched-field processing: performance in shallowwater

An issue of concern for matched-field processing is the strong dependence between performance and precise knowledge about the environmental parameters. A robust matched-field processor based on minimax robust filtering methods was developed. Here, simulation methods are employed to evaluate the performance of the minimax robust method as well as other robust methods for a range-independent shallow water environment. The performance of the robust methods is compared with that of the nominal processor, that is, the processor based on a single set of environmental parameters thought to be closest to the actual. The matched-field processing performance is evaluated in terms of the peak-to-sidelobe ratio. The simulation results indicate that the robust methods provide significant performance improvements over the nominal processor in the presence of uncertainty in water column sound speed, channel depth, and sound speed in the bottom     

Testing and evaluation of an integrated GPS/INS system for smallAUV navigation

A Small Autonomous Underwater Vehicle Navigation System (SANS) is being developed at the Naval Postgraduate School. The SANS is an integrated Global Positioning System/Inertial Navigation System (GPS/INS) navigation system composed of low-cost and small-size components. It is designed to demonstrate the feasibility of using a low-cost strap-down inertial measurement unit (IMU) to navigate between intermittent GPS fixes. The present hardware consists of a GPS/DGPS receiver, IMU, compass, water speed sensor, water depth sensor, and a data processing computer. The software is based on a 12-state complementary filter that combines measurement data from all sensors to derive a vehicle position/orientation estimate. This paper describes hardware and software design and testing results of the SANS. It is shown that results from tilt table testing and bench testing provide an effective means for tuning filter gains. Ground vehicle testing verifies the overall functioning of the SANS and exhibits an encouraging degree of accuracy     

A comparison of inter-frame feature measures for robust objectclassification in sector scan sonar image sequences

This paper presents an investigation of the robustness of an inter-frame feature measure classifier for underwater sector scan sonar image sequences. In the initial stages the images are of either divers or remotely operated vehicles (ROV's). The inter-frame feature measures are derived from sequences of sonar scans to characterize the behavior of the objects over time. The classifier has been shown to produce error rates of 0%-2% using real nonnoisy images. The investigation looks at the robustness of the classifier with increased noise conditions and changes in the filtering of the images. It also identifies a set of features that are less susceptible to increased noise conditions and changes in the image filters. These features are the mean variance, and the variance of the rate of change in time of the intra-frame feature measures area, perimeter, compactness, maximum dimension and the first and second invariant moments of the objects. It is shown how the performance of the classifier can be improved. Success rates of up to 100% were obtained for a classifier trained under normal noise conditions, signal-to-noise ratio (SNR) around 9.5 dB, and a noisy test sequence of SNR 7.6 dB     

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     

基于地球系统模式的局地化粒子滤波器与集合卡尔曼滤波器同化实验

粒子滤波器(PF)是一种非常具有应用前景的非线性资料同化方法。但由于其算法本身存在的粒子退化问题,目前尚未被广泛地应用于大型地球物理模式。目前主流的集合同化系统仍然倾向于使用集合卡尔曼滤波器(EnKF)及其衍生方法。一种新近被提出的局地化粒子滤波器(LPF)在经典的粒子滤波器算法中引入局地化技术,可以使用较小的计算成本有效地避免退化问题,具有非常大的业务应用潜力。本文在全耦合的通用地球系统模式中开展了LPF和EnKF的同化实验,同化资料为模拟的卫星海表温度资料。着重考察了不同局地化参数对两种方法的不同影响,对比了局地化粒子滤波器与集合卡尔曼滤波器的同化效果差异。比较的结果表明,LPF的同化效果对于局地化参数的选择非常敏感,在使用最优局地化参数的条件下,LPF能达到与EnKF相当甚至优于后者的同化效果,并具有较大的改进空间。     

Digital signal processing for precision wide-swath bathymetry

A mathematical model is formulated which accurately represents the envelope function of bottom return signals received from a number of spatial directions comprising a wide swath. The bottom return signals are processed utilizing a digital nonrecursive matched filter whose coefficients are tapered using a Tukey window. High-speed convolution employing the fast Fourier transform is examined for implementation of the digital matched filtering operation. Computer simulation of the signal processing system indicates that, even in the presence of considerable background and fluctuation noises, the processor provides an output signal having a well-defined peak. The error in time of arrival is found to be less than 3 ms, corresponding to an error in depth of less than 0.1 percent, for an average signal-to-noise ratio of 15 dB and a vertical ocean depth of 12 000 ft (3.7 km). These performance figures apply to the most difficult case of mapping at angles ofpm 45degoff vertical.