Data fusion and tracking using HMMs in a distributed sensor network

This work deals with the problem of multiple target tracking, from the measurements made on a field of passive sonars activated by an active sonar (multistatic network). The difficulties encountered then are of two kinds: each sensor alone does not provide full observability of a target, and multiple, possibly maneuvering targets moving in a cluttered environment must be dealt with. The algorithm presented here is based on a discrete Markovian modelization of the targets evolution in time. It starts with a fusion of the detections obtained at each measurement time. Tracking and target motion analysis (TMA) are next achieved thanks to dynamic programming (DP). This approach leads to multiple and maneuvering target tracking, with few assumptions; for instance, the use of deterministic target state models are avoided. Simulation results are presented and discussed.     

On Sonar Signal Analysis

Systems which utilize acoustic energy to explore an undersea environment are called sonars. This introductory and tutorial paper presents a discussion of active sonar signal analysis concentrating upon sinusoidal, linear FM, and pseudorandom echolocation pulses. Many previously published results concerning sonar signals and their haracteristics are integrated, collected, and presented in a unified form such as to portray typical signal design considerations.     

主/被动联合多基地航空搜潜范围分析

 在主/被动联合多基地航空搜潜条件下,根据声纳、浮标、潜艇的位置关系,推导出了对目标定位的数学模型,并结合主/被动声纳方程,建立了目标与主动声纳和浮标之间的位置关系、主动声纳的最大传输距离、多基地搜潜的搜潜范围和定位范围等数学模型,在此基础上,分析了搜潜范围与主动声纳和浮标距离之间的关系、目标与主动声纳和目标与浮标距离之间的关系、浮标位置与搜潜范围和定位范围之间的关系等,获得了有益的结果。     

基于先验目标航向的主/被动联合多基地航空搜潜建模与仿真

利用主动吊放声纳与被动浮标组成多基地航空声纳对目标进行搜索,可节约搜索时间,有效提高搜潜效率。针对已知目标的大概航向,在有限范围内确定目标存在区的情况下,建立了多基地搜潜范围模型、单机吊放声纳和浮标的主/被动联合多基地搜潜模型、潜艇运动模型,仿真分析了潜艇初始航向、海洋环境噪声、搜索样式等因素对联合搜索概率的影响。结果表明,潜艇初始航向角度对单机吊放声纳和浮标的联合搜索概率影响较小,海洋环境噪声的变化对单机吊放声纳和浮标的联合搜索概率影响较大。     

改善三元子阵测距精度方法研究

在水声领域,三元子阵测距、目标运动分析(TMA)和匹配场处理(MFP)是被动噪声测距的3种主要技术。文中以三元子阵测距声呐为研究对象,从波束形成、相关系数处理、测向精度改进等方面讨论提高时延估计精度的方法,对工程应用具有一定的参考价值。     

Low observable target motion analysis using amplitude information

In conventional passive and active sonar system, target amplitude information (AI) at the output of the signal processor is used only to declare detections and provide measurements. We show that the AI can be used in passive sonar system, with or without frequency measurements, in the estimation process itself to enhance the performance in the presence of clutter where the target-originated measurements cannot be identified with certainty, i.e., for “low observable” or “dim” (low signal-to-noise ratio (SNR)) targets. A probabilistic data association (PDA) based maximum likelihood (ML) estimator for target motion analysis (TMA) that uses amplitude information is derived. A track formation algorithm and the Cramer-Rao lower bound (CRLB) in the presence of false measurements, which is met by the estimator even under low SNR conditions, are also given. The CRLB is met by the proposed estimator even at 6 dB in a cell (which corresponds to 0 dB for 1 Hz bandwidth in the case of a 0.25 Hz frequency cell) whereas the estimator without AI works only down to 9 dB. Results demonstrate improved accuracy and superior global convergence when compared with the estimator without AI. The same methodology can be used for bistatic radar     

Data association for deghosting in Y-shaped passive linear array sonars

This paper deals with data association using three sets of passive linear array sonars (PLAS) geometrically positioned in a Y-shaped configuration, fixed in an underwater environment. The data association problem is directly transformed into a 3D assignment, which is known to be NP hard. For generic passive sensors, it can be solved using conventional algorithms, while in PLAS, it becomes a formidable task due to the presence of bearing ambiguity. Thus, the central issue of the problem in PLAS is how to eliminate the bearing ambiguity without increasing tracking error. To solve this problem, the 3D assignment algorithm used the likelihood value of only those observed bearing measurements is modified by incorporating frequency information in consecutive time-aligned scans. The region of possible ghost targets is first established by the geometrical relation of PLAS with respect to target. The ghost targets are then confirmed and eliminated by generating multiple observations in consecutive scans. Representative simulations demonstrate the effectiveness of the proposed approach.     

Waveform fusion in sonar signal processing

In active sonar systems, proper selection of the transmitted waveform is critical for target detection and parameter estimation, especially with the existence of clutter (reverberation). Two commonly used waveforms (constant frequency (CF) and linear frequency modulated (LFM)) are studied. Their characteristics are complementary both with respect to their accuracies and their sensitivity to the blind zero-Doppler ridge. Several fusion schemes of the two kinds of waveforms are explored and fusion results are studied both analytically and from simulation. It is concluded that fusion of the information of different waveforms can be not only more robust, but in some cases outright preferable, in term of detection probability and estimation accuracy.     

基于序贯关联算法的多目标无源跟踪

基于序贯关联算法,对多目标无源跟踪问题进行了研究。在只有角度信息可以利用的情况下,首先,利用波门技术对各个无源传感器角度测量数据进行关联和滤波,形成参数航迹;然后,将各个无源传感器的参数航迹送到融合中心进行关联配对,并在关联过程中通过构造关联质量函数对参数航迹的关联历史情况进行度量,解决参数航迹关联模糊问题;最后,通过对关联成功的参数航迹进行交叉定位,给出多个不同目标的位置信息,实现分布式无源系统对多目标的数据关联和跟踪,并通过仿真分析,对算法的有效性和可行性进行验证。     

HT-TBD在水下目标被动检测中的应用

在弱目标检测研究中,HT-TBD检测算法是 1种有效的理论方法。针对现有水下弱目标被动检测的难题,提出 1种适用于水下目标被动检测的 HT-TBD算法。首先,阐述 HT-TBD检测思路,在分析声呐浮标检测组检测预处理基础上,研究基于 TBD理论和 Hough变换的水下目标被动检测算法;其次,围绕浮标阵型适用场景,分析探测设备指标、环境场地指标、目标指标及干扰指标,给出拦截阵和覆盖阵 2类试验方案及步骤;最后,在新安江水库对 2类试验场景数据进行采集和预处理。结果表明:通过实测数据和 MATLAB仿真验证了 HT- TBD检测算法在水下弱目标检测的可行性和有效性。     

Frequency line tracking using HMM-based schemes [passive sonar]

This paper deals with fluctuating line tracking, present on the so-called lofargram (low frequency analysis and recording) encountered in any passive sonar system. Considering such a line as a random walk modeled by a first-order Markov chain, we have recourse to the hidden Markov models (HMMs) arsenal. More precisely, we propose to track a frequency line with Viterbi and forward-backward algorithms. The originality of this work comes from the fact that a "probabilistic integration of the spectral power" approach allows us to construct a signal-to-noise (SNR)-knowledge-free method. Intensive simulations reveal no loss of performance.     

主被动多传感器多目标状态信息融合

研究了主被动多传感器多目标状态信息融合问题。针对被动式跟踪的特点,借助主动跟踪的距离通道值,提出类主动的被动式跟踪。在此基础上提出主被动串联状态信息融合和并联状态信息融合算法。仿真结果表明两种状态信息融合方法都可以大大提高跟踪精度,同时还可以提高系统的可靠性。     

Track formation with bearing and frequency measurements in clutter

Target motion analysis from a narrowband passive sonar that yields bearing and frequency measurements in the presence of false detections (clutter) in a low-SNR (low signal-to-noise ratio) environment is discussed. The likelihood function used to compute the maximum likelihood estimation of the track parameters (localization and frequency) incorporates the false alarms via the probabilistic data association technique. The Cramer-Rao lower bound is calculated and results obtained from simulations are shown to be compatible with it. A test of track acceptance is also presented     

一种分布式异步航迹融合算法

在多被动传感器目标跟踪中,融合中心处理的信息一般是同步的,然而实际情况并非如此。另外,一些被动传感器只能得到目标的方位信息,无法单独形成有效航迹,这就需要将各传感器数据同步到相同时刻,然后应用同步融合算法。针对被动传感器探测系统,采用传感器到传感器融合和系统到传感器融合的分布式融合结构,并对各局部传感器引入全局反馈,对相关信息采用协方差交叉算法进行处理,完成被动传感器异步数据的融合,仿真结果表明,该算法具有较好的融合效果。     

Doppler-Tolerant Classification of Distributed Targets -- A Bionic Sonar

Sonar echo analysis that is not affected by relative motion between target, transmitter, and receiver is discussed. Motion-tolerant measurement and recognition of range-distributed targets involves: 1) a determination of the effects of range rate upon echoes from non-planar reflectors and 2) the derivation of a signal, filter bank, and target parameterization scheme that is insensitive to those effects. The appropriate system is derived, simulated with a computer, and tested with actual echoes from various targets. The system's signals and filters are very similar to those found in biological sonars.     

A formulation of multitarget tracking as an incomplete data problem

Traditional multihypothesis tracking methods rely upon an enumeration of all the assignments of measurements to tracks. Pruning and gating are used to retain only the most likely hypotheses in order to drastically limit the set of feasible associations. The main risk is to eliminate correct measurement sequences. The probabilistic multiple hypothesis tracking (PMHT) method has been developed by Streit and Luginbuhl in order to reduce the drawbacks of "strong" assignments. The PMHT method is presented in a general mixture densities perspective. The Expectation-Maximization (EM) algorithm is the basic ingredient for estimating mixture parameters. This approach is then extended and applied to multitarget tracking for nonlinear measurement models in the passive sonar perspective.     

Low-Loss Almost Constant False-Alarm Rate Processors

Conventional normalizing constant false-alarm rate (CFAR) circuits use the same configurations when detecting targets in interference regions and in clear regions. The CFAR penalty incurred in the clear region can be reduced by using CFAR processors that recognize the region is clear so that normalization is not necessary. An analysis of the target-detection performance for a particular modified CFAR processor, for an active-radar sensor, and for a passive infrared (IR), or sonar, sensor is given. It is shown that the decreased CFAR penalty in the clear is coupled with an increase of false-alarm rate in the clutter regions.     

基于C8051F020的绞车键盘模拟训练系统的设计与实现

为方便声纳员进行操作训练,设计、开发了一种能够脱离实装设备的吊放声纳绞车键盘模拟训练系统,绞车键盘操作的画面布局及键盘布局等与实装绞车键盘一致。同时,绞车键盘通过控制变频器带动电机以驱动绞车,可以逼真地模拟实际对绞车的操作,模拟也可以对特定条件下的训练方案进行设定,以提高声纳操作人员的训练水平。     

反潜直升机缆位缆高控制系统实时仿真研究

通过反潜直升机吊放声纳控制系统的半实物实时仿真系统研究,建立了半实物仿真的结构和直升机与缆 数学模型,进行了相关硬件设备的研制,并编写了实时仿真软件,进行降多种条件下的半实物实时仿真研究工作。通过仿真验证了直升机上的吊放声纳飞行控制系统满足性能指标要求,仿真结果同最后实飞空测结果保持了一致。     

Bearings-only and Doppler-bearing tracking using instrumentalvariables

In bearings-only tracking (BOT) or Doppler and bearing tracking (DBT), both common passive sonar problems, the measurement equations are nonlinear. To apply the Kalman filter, it is necessary either to linearize the equations or to embed the nonlinearities into the noise terms. The former sometimes leads to filter divergence, while the latter produces biased estimates. A formulation of BOT and DBT which has a constant state vector and simplifies the tracking problem to one of constant parameter estimation is given. The solution is by the instrumental variable method. The instrumental variables are obtained from predictions based on past measurements and are therefore independent of the present noisy measurements. The result is a recursive unbiased estimator. The theoretical developments are verified by simulation, which also shows that the formulation leads to near optimal estimators whose errors are close to the Cramer-Rao lower bound (CRLB)