Asymptotic detection performance of discrete power and higher-order spectra estimates

Several detection statistics are compared in the frequency domain based on the asymptotic probability of detection (APD) criterion. They include second-order, fourth-order, normalized fourth-order, and kurtosis estimates. The results show that for randomly occurring signals which can be characterized as non-Gaussian, the fourth-order, normalized fourth-order, and kurtosis estimates can have higher asymptotic probability of detection levels compared with second-order estimates. But only for the normalized fourth-order and kurtosis estimates do the results seem significant. Moreover, if a second-order estimate of the noise is available to normalize a fourth-order estimate of signal and noise, the resultant normalized fourth-order estimate has higher asymptotic probability of detection levels even for Gaussian signals. This result holds only when there is a significant positive covariance between the numerator and the normalizing noise sample in the denominator. On the other hand, if an independent noise sample is used to normalize a second-order or fourth-order estimate, the overall performance based on the asymptotic probability of detection will be degraded compared with the unnormalized second-order or fourth-order estimates, respectively.     

On estimating random amplitude-modulated harmonics using higherorder spectra

Additive as well as multiplicative noise may occur when acoustic waves propagate through the ocean. Second-order spectral methods fail to retrieve frequencies of such random amplitude modulated harmonic time series, especially when the multiplicative noise is broadband. An existing fourth-order method assumes real Gaussian multiplicative and additive noise. A novel approach is proved herein to impose no constraints on the distribution or the color of the disturbances. It relies on fourth-order special cumulant or moment slices. In particular, the fourth-order moment spectrum is shown to offer computational advantages. Extension to multicomponent models and generalizations to alternative higher order moments are also provided. Simulations corroborate the theoretical results     

Range and Doppler information from fourth-order spectra

In an active sonar system setting, a novel method is evaluated that extracts range and Doppler information from a Doppler-spread active sonar echo. The Doppler spreading is based on H. Van Trees' (1971) Gaussian amplitude modulating model, and the new method is based on the Fourier transform of a special case of the fourth-order cumulant. Specifically, from the envelope of the Gaussian amplitude modulated echo of a transmitted coded pulse train, the second-order spectrum and the Fourier transform of a special case of the fourth-order cumulant are derived and analyzed for this ability to extract range and Doppler information. It is shown that the method can theoretically extract range and Doppler information without degradation. The reason for this result is that a special case of the fourth-order cumulant is independent of the covariance of the Gaussian amplitude modulating function. These methods are also simulated and compared with the simulated results of the range-Doppler ambiguity function. This shows that the ambiguity function and the second-order spectrum are degraded due to the Gaussian amplitude modulation. The results are further demonstrated by simulating the three range-Doppler extraction methods for the received echo in noise     

Statistics of biological noise and performance of generalizedenergy detectors for passive detection

Underwater noise due to snapping shrimp is highly impulsive, and often dominates the ambient noise environment of warm, shallow waters at frequencies above 1 kHz. We report here on the statistics of bandpass snapping shrimp noise data, and on the modeling of the joint distribution of the in-phase and quadrature components using bivariate versions of the generalized Gaussian (GG), generalized Cauchy, and Gaussian-Gaussian mixture models. We evaluate the performance of several generalized energy detectors for passive bandpass detection, by inserting stochastic signals into the noise data. Detection thresholds were measured for an integration time of 0.5 s and false alarm probabilities down to 1%. The locally optimum detector based on the mixture model gave the best weak signal detection performance, with an 8 dB reduction in detection threshold over conventional energy detection. A significance test detector based on the GG model performed 1-2 dB worse, but exhibited better strong signal performance     

目标触底瞬态地震波信号的检测

目标触底过程中通常会产生强烈的瞬态地震波信号,通过对此类地震波信号的监测、处理和分析,能够帮助判断该信号的产生是否是由异常活动产生的,并且能够根据信号分析相关信息,实现早期预警, 从而做出快速响应。 由于双谱检测具有很好的抗高斯干扰能力,对高斯平稳随机过程和试验模拟目标触底瞬态地震波信号的双谱特性进行了分析,并在高斯背景中对试验采集的瞬态信号进行了检测仿真,仿真试验结果表明:在高斯背景的干扰下,双谱检测能够有效实现对瞬态信号的检测^[1] 。     

Functional inputs to passive correlation detectors for oscillatorytransient signals

This research investigates whether passive detection of transient signals can be improved by replacing received signals with functionals of the received signals in correlation detectors. Specifically, this paper assesses the impact of using energy spectrum and autocorrelation functional inputs to the cross-correlation (energy), bicorrelation, and tricorrelation detectors. Test signals with differing autocorrelation and energy spectrum properties are used in computer simulations with independent Gaussian noise to evaluate detector performance. Detection results are presented for the case when only two channels of input data are available to form the correlations, as well as the case when three and four channels of input data are available to form the higher order correlations. In the former case, it is shown that detection performance can be improved for the narrow-band signals by using the energy spectrum and autocorrelation functional inputs rather than the original received signal. In the latter case, it is shown that detection performance can be improved by using the autocorrelation input for the broadband signal and the energy spectrum input for the narrow-band signals, and that the tricorrelation detector performs best for the signals tested     

基于窄带混合高斯噪声的最佳检测

论文首先研究高斯柯西卷积噪声模型和窄带混合高斯噪声模型用来对混响建模,前者主要用于仿真分析,而后者因其参数有明确物理意义且可通过样本序列估计得到,因此被用于海洋的工程实现.文章重点研究混合高斯噪声背景下确知信号的非高斯最佳检测器的构造,并对检测器进行了仿真.验证结果表明混合高斯噪声背景下确知信号的非高斯最佳检测器检测性能优于常规的匹配滤波器3～4.5 dB.     

Optimal and Near-Optimal Signal Detection in Snapping Shrimp Dominated Ambient Noise

The optimal detection of signals requires detailed knowledge of the noise statistics. In many applications, the assumption of Gaussian noise allows the use of the linear correlator (LC), which is known to be optimal in these circumstances. However, the performance of the LC is poor in warm shallow waters where snapping shrimp noise dominates in the range 2-300 kHz. Since snapping shrimp noise consists of a large number of individual transients, its statistics are highly non-Gaussian. We show that the noise statistics can be described accurately by the symmetric alpha-stable family of probability distributions. Maximum-likelihood (ML) and locally optimal detectors based on the detailed knowledge of the noise probability distribution are shown to demonstrate enhanced performance. We also establish that the sign correlator, which is a nonparametric detector, performs better than the LC in snapping shrimp noise. Although the performance of the sign correlator is slightly inferior to that of the ML detector, it is very simple to implement and does not require detailed knowledge of the noise statistics. This makes it an attractive compromise between the simple LC and the complex ML detector     

A Statistical Analysis of the Detection Performance of a Broadband Splitbeam Passive Sonar

An operational passive sonar is required to detect signals from sources, which are subject to spatial and temporal coherence losses via modifications by the ocean environment. Furthermore, these signals are to be detected in the presence of frequency-dependent correlated noise fields. For a system which employs splitbeam cross-correlation processing, the spatial and spectral properties of the signal and noise are of significant import. Therefore, the exact probability density and cumulative distribution functions of the N-sampled correlator outputs of a splitbeam broadband passive sonar are derived for the case of Gaussian inputs which are described by arbitrary cross-spectral density matrices. The validity of approximating the exact probability density function (pdf) as a Gaussian distribution is investigated. The effect of signal coherence loss and noise correlation on the detection performance is considered and the associated processing loss is expressed as a degradation factor within the detection threshold equation     

A novel CFAR tonal detector using phase compensation

A novel tonal detector is presented in this paper. The detector uses phase compensation for detecting sinusoidal signal with unknown amplitude, frequency, and phase in complex Gaussian noise with unknown variance. We analyze the statistical properties of the discrete Fourier transform (DFT) of the observations and consider the leakage effect. Then we develop the detector by using generalized likelihood ratio test (GLRT). The new detector fully utilizes the phase information of the signal and achieves constant false alarm rate (CFAR) property. Theoretical analysis and simulation results show its improvement in detection performance.     

基于高斯与小波的机载测深LiDAR波形分解算法

波形分解是机载测深LiDAR数据处理的关键环节,为水深计算、底质类型反演和水体浑浊度分析等提供基础信息。针对传统测深LiDAR波形分解算法受噪声干扰严重、对微弱及叠加信号分解不准确的问题,提出一种新的波形分解算法。对原始波形经小波滤波后,计算滤波前后尾段波形的差异,估计回波信号的噪声;利用高斯模型,从原始波形数据中不断分解出经LM算法优化参数后的波形分量,直到剩余波形中最大峰值与优化后的参数小于一定阈值。通过南海实测数据进行验证,实验结果表明:该算法分解弱回波能力强,不论在浅水(回波发生叠加)还是深水,其分解精度均优于传统算法。     

Optimum and Suboptimum Detector Performance for Signals in Cyclostationary Noise

The detection of known and partially known signals in additive white Gaussian uonstationary noise is considered, with primary attention to the ease where the time-varying noise intensity parameter N_{o}(t) is a periodic function. Optimum receiver structures are derived for three detection cases, namely completely known signals, sinusoids with random phase, and sinusoids with both random amplitude and phase. It is demonstrated that optimum receiver performance can be achieved only if proper synchronization to the noise intensity N_{o}(t) is accomplished. Large performance penalties can be demonstrated when an improperly synchronized receiver is used. Consequently, suboptimum receivers that ignore the noise intensity time variations and therefore require no synchronization, have been considered, and their performance compared to their optimum counterparts. Depending on the type of time-varying noise intensity being considered, results show that performance differences between optimum and suboptimum receivers can be negligible in some cases, and yet can be substantial in other cases. Several examples have been worked out using two different forms for N_{o}(t) and corresponding performance evaluations have been carried out and presented graphically in terms of receiver error probability as a function of signal-to-noise ratio.     

Invariants of Spectral Moments and their Degeneracy for a Gaussian Surface

The transformation and symmetry properties of surface derivatives and spectral moments under rotation of the coordinate axes are examined. It is shown that the moments as well as the derivatives are generally represented in terms of their rotational invariants. For a Gaussian surface, which is characterized by additional symmetry of correlation matrices, the even moments higher than the second order are degenerate; i.e., only three of them are independent, and only two invariants are nonzero. Specific properties of spectrum symmetry and the joint statistical distribution of the mean and differential curvatures are found in this case. As an application of these results to observation of the sea surface, a simple optical method is suggested for simultaneous remote-sensing measurement of the second- and fourth-order moments. This method is based on the count of reversely reflected light impulses, arising from sea-surface scanning by the continuous laser radiation.     

The use of spectral information in optimal detection of a source inthe presence of a directional interference

The detection of a passive sonar target in the presence of ambient noise and a plane wave interference is discussed. Intuitively, such a detector consists of a spatial filter which nulls the interference, followed by a temporal filter. In this paper we study the role of the a priori knowledge of the spectrum of the interference and/or signal in improving detector performance. We develop three different generalized likelihood ratio test (GLRT) detectors, resulting from different cases of prior spectral information. We show that, for all cases of known/unknown source and/or interference power spectrum, the GLRT detectors are, as expected, null steering systems. The depth and shape of the null, as well as the postbeamforming temporal filter, are different and are functions of the a priori known spectrum. Under the assumption that all signals and noise are zero-mean Gaussian processes, we analyze the performance of the different detectors and we exploit their dependency on the array beampattern, as well as on the source and interference signal-to-noise ratio. This analysis serves to identify scenarios where the use of prior spectral information leads to significant performance improvement     

Signal detection for communications in the underwater acousticenvironment

Signal detection is a critical stage in the implementation of any effective communications system. The underwater acoustic environment, particularly in the presence of underwater vehicles, presents significant challenges to reliable detection without excessive false alarms. While there is often sufficient signal-to-noise ratio with respect to stationary broad-band background noise to permit reliable operation, the presence of strong event-like interference signals such as narrow-band signals and impulsive broad-band signals complicates the detection problem significantly. Frequency-hopped signals interleaved with quiescent bands are proposed as the basis of a robust detection system. These signals also make robust detection possible in a multi-access communications system. Two new detection algorithms that exploit the particular structure of these frequency-hopped signals are developed and their performance is analyzed. This analysis uses a modification of the doubly noncentral F-distribution that has not been used previously for such analysis. This distribution makes possible the direct calculation of probabilities of detection and false-alarm under interference and signal scenarios that cannot be analyzed using the better known noncentral F-distribution. With this analysis, the two developed detectors are shown to offer superior performance to that of either the CFAR detector or the binary data sequence detector. Experimental data confirms the theoretically derived results     

基于图像处理的回声定位信号检测方法

鲸豚类海洋哺乳动物发出的回声定位信号是一种频率较高的短时脉冲信号,研究回声定位信号检测方法有助于快速、准确地检测海洋哺乳动物发声,进而更好地保护海洋哺乳动物.本文提出了一种基于图像处理的鲸豚类动物回声定位信号检测方法.该方法首先对收集到的数据进行分帧,计算每帧信号的时频图;使用Frangi滤波器对时频图进行滤波,以降低...     

An Effective Control System of Thrust and Moment Modulation for a Dynamically Positioned Vessel

Dynamic positioning (DP) is an operation method whereby the position of a surface vessel is maintained in close proximity to a required position in the horizontal plane through the controlled application of forces and moments generated by purposely installed thrusters. When estimating thrust, this kind of conventional control system often uses many acceleration sensors, velocity sensors, environment sensors, and filters. Usually, these sensors have measured electrical errors. To reduce the number of sensors used and to decrease the measurement errors, this article presents an effective control system for estimating thrust and moment commands, which is based on energy and impulsemomentum principles. Donha and Brinati's example is followed to verify the feasibility of the present control system, which performs semisubmersible platform positioning using an LQG controller, and the results are feasible and economical. A simulated coring vessel marine positioning in southern Taiwan is presented, which can estimate the counterthrust and moment commands, and the complex environmental forces and moments are described. The results can provide a valuable control system for dynamically positioned vessels.     

An Effective Control System of Thrust and Moment Modulation for a Dynamically Positioned Vessel

Dynamic positioning (DP) is an operation method whereby the position of a surface vessel is maintained in close proximity to a required position in the horizontal plane through the controlled application of forces and moments generated by purposely installed thrusters. When estimating thrust, this kind of conventional control system often uses many acceleration sensors, velocity sensors, environment sensors, and filters. Usually, these sensors have measured electrical errors. To reduce the number of sensors used and to decrease the measurement errors, this article presents an effective control system for estimating thrust and moment commands, which is based on energy and impulsemomentum principles. Donha and Brinati's example is followed to verify the feasibility of the present control system, which performs semisubmersible platform positioning using an LQG controller, and the results are feasible and economical. A simulated coring vessel marine positioning in southern Taiwan is presented, which can estimate the counterthrust and moment commands, and the complex environmental forces and moments are described. The results can provide a valuable control system for dynamically positioned vessels.     

Sea surface temperature retrieval based on simulated microwave polarimetric measurements of a one-dimensional synthetic aperture microwave radiometer

Compared with traditional real aperture microwave radiometers, one-dimensional synthetic aperture microwave radiometers have higher spatial resolution. In this paper, we proposed to retrieve sea surface temperature using a one-dimensional synthetic aperture microwave radiometer that operates at frequencies of 6.9 GHz, 10.65 GHz,18.7 GHz and 23.8 GHz at multiple incidence angles. We used the ERA5 reanalysis data provided by the European Centre for Medium-Range Weather Forecasts and a radiation transmission forward model to calculate the model brightness temperature. The brightness temperature measured by the spaceborne one-dimensional synthetic aperture microwave radiometer was simulated by adding Gaussian noise to the model brightness temperature.Then, a backpropagation(BP) neural network algorithm, a random forest(RF) algorithm and two multiple linear regression algorithms(RE1 and RE2) were developed to retrieve sea surface temperature from the measured brightness temperature within the incidence angle range of 0°–65°. The results show that the retrieval errors of the four algorithms increase with the increasing Gaussian noise. The BP achieves the lowest retrieval errors at all incidence angles. The retrieval error of the RE1 and RE2 decrease first and then increase with the incidence angle and the retrieval error of the RF is contrary to that of RE1 and RE2.     

Detection of transient signals in multipath environments

This research examines methods for detecting unknown transient waveforms that are contaminated by noise. The sensitivity of the performance levels of the energy detector and the lack of knowledge about the structure of the transient waveform motivate the examination of other moment- or spectra-based detection techniques. We examine the performance of a bispectral energy detector and show that its performance will degrade if the bispectra is smoothed and that signals with no bispectral content can be detected if the bispectra is not smoothed. Further, it is shown that the performance levels of the bispectral detector are slightly better, and slightly less sensitive, than those of the energy detector for the multipath linear frequency modulated signal. Finally, the performance levels of narrowband implementations of the energy and bispectral energy detectors are compared. It is shown that for a large enough sample, the performance levels of the bispectral detector are nearly as good as those of the optimal energy detector for the single narrowband signal case. However, when the received waveform contains multiple narrowband components, the narrowband bispectral detector performs slightly better than the energy detector