Passive systems theory with narrow-band and linear constraints: Part I--Spatial diversity

This paper studies passive problems where the receiver extracts from the source radiated signature information concerning the parameters defining the relative source/receiver geometry. A model encompassing the fundamental global and local characteristics for passive positioning and navigation is presented. It considers narrow-band signals, imposes linear constraints on the geometry, and exhibits explicitly the symmetry between the space and time aspects. The analysis concentrates on questions of global geometry identifiability, emphasizing the passive global range acquisition. The maximum-likelihood processor is analyzed by studying the ambiguity structure associated with inhomogeneous passive narrowband tracking. Bounds on the global and local mean-square error performance are studied and tested via Monte Carlo simulations. By considering two limiting geometries, a distant and a close observer, simple approximate expressions for the mean-square errors are presented and compared to the exact bounds. Herein the study is restricted to stationary geometries where the source is located by an extended array (spatial diversity). Subsequent papers generalize the study to moving sources (temporal diversity) and to coupled geometries.     

Passive systems theory with narrow-band and linear constraints: Part III -- Spatial/Temporal diversity

This is the last of a series of three papers studying the theory of passive systems. The model assumes that i) the narrow-band signals are transmitted through a Rayleigh channel, ii) the observing array is geometrically linear, and iii) the source motion is deterministic. Ranging techniques based on synchronized measurements of the travel time delay are precluded by the incoherent phase model considered. The paper explores alternative methods that process the phase modulations induced on the signal by the extended geometry and relative dynamics. The present work applies maximum likelihood theory to design the receiver, being concerned with the global identifiability of all parameters defining the relative source/receiver geometry and dynamics. The emphasis is placed on the passive range global acquisition. In contradistinction with the previous papers, where the time stationarity (Part I) or the space homogeneity (Part II) lead to a one-dimensional processor, here the receiver involves processing over both domains. The paper considers the issues of space/time factorability and coupling arising in nonhomogeneous passive tracking. The cross coupling, resulting in more complex filters, improves the receiver acquisition capability. Resorting to Taylor's series type studies, the paper quantifies these improvements, as well as the receiver's mean square error performance, in terms of intuitively satisfying analytical expressions.     

VLF source localization with a freely drifting acoustic sensorarray

The source localization and tracking capability of the freely drifting Swallow float volumetric array is demonstrated with the matched-field processing (MFP) technique using the 14-Hz CW data collected during a 1989 float experiment conducted in the northeast Pacific. Initial MFP of the experimental data revealed difficulties in estimating the source depth and range while the source azimuth estimate was quite successful. The main cause of the MFP performance degradation was incomplete knowledge of the environment. An environment adaptation technique using a global optimization algorithm was developed to alleviate the environmental mismatch problem, allowing the ocean-acoustic environment to be adapted to the acoustic data in a matched-field sense. Using the adapted environment, the 14-Hz source was successfully localized and tracked in azimuth and range within a region of interest using the MFP technique at a later time interval. Two types of environmental parameters were considered, i.e., sound speed and modal wave number. While both approaches yield similar results, the modal wave number adaptation implementation is more computationally efficient     

Passive Doppler-bearing tracking using a pseudo-linear estimator

In this paper an explicit pseudo-linear estimator for Doppler-bearing tracking is proposed. It overcomes the problems with the bias of earlier pseudo-linear estimators and with the nonlinear frequency measurement equation by using another representation than the Cartesian one and by using the logarithm of the frequency, respectively. It is fast, inherently stable, and easy to implement. The Doppler shift is, for a nonmoving own-ship, determined by the target velocities, while the bearing rate is determined by the same velocities divided by the range. The special representation in this paper uses this difference in behavior to give fast and bias free estimation of the range. Instead of iterating a weighted feast squares problem using bearing and frequency measurements simultaneously, the true bearings and the course are estimated in a bearings only step followed by a frequency only step, which estimates range and frequency. The range estimate then gives the speed estimate. Modifications for scenarios with multiple emitted frequency lines and/or for frequency lines that disappear during parts of a scenario are shown     

Acoustic Detection and Localization of a Turboprop Aircraft by an Array of Hydrophones Towed Below the Sea Surface

The acoustic spectrum of a propeller-driven aircraft is dominated by a series of spectral lines that are harmonically related to the blade rate (which is equal to the product of the propeller rotation rate and the number of blades on the propeller). We show that an array of acoustic sensors towed below the sea surface can be used for the passive detection and localization of such an aircraft. The acoustic energy from an aircraft is found to reach the subsurface sensors via two propagation paths: a bottom reflection path that enables the aircraft to be detected at long ranges, and a direct path that is present only when the aircraft passes overhead. For each of these paths, the observed variation with horizontal range of the Doppler shift in the blade rate closely matches the variation predicted by the simple model presented in this paper. Good agreement between theory and experiment is also obtained for the variation with horizontal range of the aircraft's apparent bearing. Thus, by using the observed Doppler shift and apparent bearing information, we were able to estimate the aircraft's horizontal range, speed, direction, and altitude.      

带乘性噪声的一类非线性系统的滤波算法

针对带乘性噪声的一类非线性系统,给出了1种带单重渐消因子的强跟踪状态滤波算法。该算法将非线性系统线性化后,采用了线性最小方差估计方法来进行状态估计,通过运用正交原理和引入渐消因子,使得滤波效果具有强跟踪的优良性能。该算法扩展了卡尔曼滤波在带乘性噪声非线性系统状态估计中的应用范围。仿真结果表明了该算法的有效性。     

Robust regression-based EKF for tracking underwater targets

In underwater target tracking applications, measurement uncertainty and inaccuracies are usually modeled as additive Gaussian noise. The Gaussian model of noise may not be appropriate in many practical systems. The non-Gaussian noise and the model non-linearity arising in a tracking system will seriously affect the tracking performance. This paper discusses one way to create a robust version of the extended Kalman filter for enhanced underwater target tracking. State estimation in the filter is done through the robust regression approach and Welsch's proposal is used in the regression process. Monte Carlo simulation results with heavy-tailed contaminated observation noise demonstrate the robustness of the proposed estimation procedure     

Tracking the velocity and position of offshore vessels and floating objects with HF Doppler transponders

Experiments with a high-frequency (HF) Doppler radar and a frequency-shifting transponder show that the velocity and position of ships or floating objects can be tracked without the need for accurate differential-position measurements. Maximum-entropy spectral analysis permits tracking during rapid maneuvers using sampling times as short as 4 s.     

Classification of transient sonar sounds using perceptually motivated features

This paper describes a novel framework for classifying underwater transient signals recorded by passive sonar. The proposed approach involves two key ideas. Firstly, a feature-selection algorithm is used to identify those acoustic features that optimally model each class of transient sound. Secondly, features that are perceptually motivated are proposed, i.e., they encode information that human listeners are likely to use in transient classification tasks. Three perceptual features are proposed, which encode timbre, the physical material of the sound source, and the temporal context (pattern) in which the transient occurred. The authors show how these features, which are computed over different temporal windows, can be combined to make classification decisions. The performance of the proposed classifier is evaluated on a corpus of transient signals extracted from passive sonar recordings. Specifically, the performance of the perceptual features is compared with spectral features and with those that encode statistics of time, frequency, and power. The present results show that the perceptual features provide valuable cues to the class of a transient. However, the best performing classifier was obtained by selecting a subset of perceptual, spectral, and statistical features in a class-dependent manner.     

深海海面目标单水听器被动测距方法与验证

基于射线理论分析了在深海情况下海面声源产生声场的频率-距离干涉结构,给出了影区内声场频率-距离干涉结构的近似理论表达式,分析得到影区内声场频域干涉周期随收发距离的增加而增大、随着接收水听器深度的增加而减小。因此由单水听器记录的声场干涉结构即可实现被动声源距离估计。在南海深海实验中观测到海面宽带噪声源在声场影区形成的声场干涉结构,对实验获得声场干涉结构的处理结果验证了深海声场影区干涉结构用于被动声源距离估计的有效性。与传统的匹配场被动定位方法相比,该方法不需要已知海底声学参数和大规模的拷贝场计算。     

Oceanic incoherent Doppler sonar spectral analysis by conventional and finite-parameter modeling methods

The spectral structure of oceanic incoherent Doppler sonar data is analyzed with Fourier and two finite-parameter modeling methods (Spectral Moment Estimation (SME) and AutoRegressive (AR)). Fourier spectral analysis, applied to long-range segments of echo return data, validates a theoretical point scattering model. It is demonstrated that Fourier spectral techniques, applied to data from incoherent sonar systems, cannot be used to probe oceanic spectral and velocity fields on the scales that frequently are important in oceanographic applications. The finite-parameter methods model the spectral structure on closely spaced range intervals. The SME method calculates the first moment of the Doppler spectrum at each range interval and the AR method provides spectral estimates at these same intervals. Trade-offs in estimating scatterer radial velocity using the various algorithms are considered. It is shown that a frequency-integrated AR technique has velocity estimation performance comparable to the SME method. In addition, the AR technique reveals that several regions of data possess asymmetric spectral structure. The implications of this spectral structure for oceanic velocity estimates are discussed.     

Single-ping target speed and course estimation using a bistatic sonar

This paper focuses on estimating the two-dimensional (2-D) target-speed vector (course and speed) using a multistatic sonar that consists of one monostatic sonar and one bistatic receiver. The speed and course estimates are obtained after a single transmission. The theory on bistatic Doppler and 2-D target-speed vector estimation is first considered and then applied to simulated and real data. The results can be used to improve classification algorithms or to feed speed information to tracking algorithms, for example.     

Tracking control for underwater vehicle-manipulator systems withvelocity estimation

In this paper, the problem of tracking a desired motion trajectory for an underwater vehicle-manipulator system without using direct velocity feedback is addressed. For this purpose, an observer is adopted to provide estimation of the system's velocity needed by a tracking control law. The combined controller-observer scheme is designed so as to achieve exponential convergence to zero of both motion tracking and estimation errors. In order to avoid representation singularities of the orientation, unit quaternions are used to express the vehicle attitude. Implementation issues are also considered and simplified control laws are suggested, aimed at suitably trading off tracking performance against reduced computational load. Simulation case studies are carried out to show the effectiveness of the proposed controller-observer algorithm. The obtained performance is compared to that achieved with a control scheme in which the velocity is reconstructed via numerical differentiation of position measurements. The results confirm that the chattering on the control commands is significantly reduced when the controller-observer strategy is adopted in lieu of raw numerical differentiation; this leads to lower energy consumption at the actuators and increases their lifetime     

基于分布式控制力矩陀螺的水下航行器轨迹跟踪控制

基于控制力矩陀螺群(CMGs)的水下航行器具有低速或零速机动的能力。采用基于分布式CMGs的水下航行器方案,并研究其水平面的轨迹跟踪控制问题。通过全局微分同胚变换将非完全对称的动力学模型解耦成标准欠驱动控制模型,并根据简化的模型构建其轨迹跟踪的误差动力学模型,将轨迹跟踪控制问题转化为误差模型镇定问题。基于一种分流神经元模型和反步法设计了系统的轨迹跟踪控制律,该控制器不需要对任何虚拟控制输入进行求导计算,且能确保跟踪误差的最终一致有界性。仿真结果表明该控制器能够实现在不依赖动力学参数先验知识的情况下对光滑轨迹的有效跟踪。     

一种基于边缘信息的车辆检测和跟踪方法

针对智能交通系统中运动车辆的检测和跟踪问题,提出1种基于边缘信息车辆检测和跟踪方法。利用背景边缘提取模板提取当前帧的精确背景边缘,进而获得前景车辆边缘,用形态学方法对其进行修复,寻找车辆的外轮廓,确定跟踪区域;由于车辆运动的特殊性,以当前帧的车速作为下一帧车速的预测值,并结合跟踪区域的外形信息进行匹配。从实验效果来看,该算法简单有效,适合于实时的车辆检测和跟踪系统。     

Fast Double Selectivity Index-CFAR Detection Method for the Multi-Beam Echo Sounder

Abstract

Seafloor terrain and water column target detection is of great significance in marine surveys. However, the complex clutter environment can dramatically affect the detection performance of a multi-beam echo sounder. To simultaneously and robustly detect the seafloor terrains and water column targets, this paper proposes a fast two-dimensional double selectivity index-constant false alarm rate (DSI-CFAR) detection method. A two-dimensional cross sliding window, which includes reference cells and guard cells, is used in this paper. The proposed method improves the detection performance by using the appropriate clutter power level estimation strategies in different directions. An exponential model is accurately built by fitting various distributions, so the DSI-CFAR detection performance is greatly ameliorated. To reduce the computational load of the method, this paper uses a fast algorithm based on the global threshold. The region of interest (ROI) is selected by the preset global threshold, and the DSI-CFAR detector is only performed in the region of interest, which significantly reduces the number of pixels that must be calculated. In this paper, the measured results of different sliding windows and CFAR detection methods validate the basic performance of the proposed method.     

Source-parameter estimation by approximate maximum likelihood and nonlinear regression

Statistical properties of certain parametric methods for array processing in wave fields are investigated. Potential applications are the classic location problem in underwater acoustics and wavenumber-spectrum analysis in geophysical work. Asymptotic normality of Fourier-transformed outputs of an array of sensors is applied to define approximate likelihood functions to be maximized for source-parameter estimation. Usually, the parameters are those of the spectral-density matrix. Liggett's estimates are approximations of maximum likelihood estimates in this sense. Another possibility is to use conditional likelihood functions. As a consequence, the source parameters can be found by solving nonlinear-regression problems. Approximate solutions of the latter, which enhance certain simple estimates by some iterations related to Fisher's scoring method, compare favorably with Liggett's estimates. Key Words-Array processing, beam forming, applications in passive sonar, radar and geophysical work; parametric methods: maximum likelihood and nonlinear regression; theoretical study and numerical experiments.     

Tracking a moving vessel from bearing measurements

This paper presents a method for tracking a distant moving target using only bearing measurements obtained from a tracking platform. The method is an improvement of the Hinich-Bloom passive tracking approach presented in [1]. The target is assumed to be moving at constant speed on a fixed heading, whereas the platform maneuvers during the measurement period. The direction cosines of the bearings are computed with respect to a rotation of the coordinate system that places 0° at the mean estimated target bearing. This is done to minimize the approximation bias due to the linearization of sine bearing as a function of inverse range and time. The coordinate system is rotated back to estimate the target coordinates. When the noise is Gaussian, the estimates of target range and heading are approximately maximum likelihood when the target's relative range is slowly varying during the observation period. In this case the mean square errors of the target parameter estimates are the smallest achievable within the order of the approximation.     

An initial assessment of the performance achieved by the Seasat-1 radar altimeter

This paper describes the results of an initial on-orbit engineering assessment of the performance achieved by the radar altimeter system flown on Seasat-1. Additionally, the general design characteristics of this system are discussed and illustrations of altimeter data products are provided. The instrument consists of a 13.5-GHz monostatic radar system that tracks in range only using a 1-m parabolic antenna pointed at the satellite nadir. Two of its unique features are a linear FM transmitter with 320-MHz bandwidth, which yields a 3.125-ns time-delay resolution, and microprocessor-implemented closed-loop range tracking, automatic gain control (AGC), and real-time estimation of significant wave height (SWH). Results presented herein show that the altimeter generally performed in accordance with its original performance requirements of measuring altitude to a precision of less than 10-cm rms, SWH to an accuracy ofpm0.5m or 10 percent whichever is greater, and ocean backscatter coefficient to an accuracy ofpm1dB, all over an SWH range of 1 to 20 m.     

基于机器学习的脉动源格林函数预报初探

自由面格林函数是边界元法求解海洋工程水动力学问题的基础,如何精确而快速地计算格林函数及其导数是水动力求解的难题。对无因次化表达的脉动点源格林函数计算建立的数据库,采用深度学习函数库Keras,对数据库进行学习,建立了神经网络预报模型,探讨了全局和局部学习及预报精度,研究了模型预报效率。研究表明机器学习模型预报的格林函数能够保证较高的精度,计算效率高于数值积分计算,低于解析函数为主的多项式逼近,为提高水动力问题求解效率,解决传统计算难题提供了新的思路。