Sonar tracking of multiple targets using joint probabilistic data association

The problem of associating data with targets in a cluttered multi-target environment is discussed and applied to passive sonar tracking. The probabilistic data association (PDA) method, which is based on computing the posterior probability of each candidate measurement found in a validation gate, assumes that only one real target is present and all other measurements are Poisson-distributed clutter. In this paper, a new theoretical result is presented: the joint probabilistic data association (JPDA) algorithm, in which joint posterior association probabilities are computed for multiple targets (or multiple discrete interfering sources) in Poisson clutter. The algorithm is applied to a passive sonar tracking problem with multiple sensors and targets, in which a target is not fully observable from a single sensor. Targets are modeled with four geographic states, two or more acoustic states, and realistic (i.e., low) probabilities of detection at each sample time. A simulation result is presented for two heavily interfering targets illustrating the dramatic tracking improvements obtained by estimating the targets' states using joint association probabilities.     

深海季节性环境变化对半会聚区尺度水面声定位影响分析

针对深海声定位受海洋环境变化影响明显、需考虑测量系统的环境适应性和宽容性设计问题,提出一种评估海水环境变化对定位性能影响的仿真分析方法,将声场计算、误差传播与交会解算联合建模,以西太平洋中纬度海域夏季和冬季环境为代表性场景讨论了季节性环境变化对定位性能的影响方式和影响程度。仿真结果表明,当接收器位于海洋近表层时,在夏季和冬季呈现出两种不同的声信道样式,夏季季节性温跃层影响下的定位精度较差,冬季表面波导影响下的定位精度相对较好,两者均方根误差(RMSE)相差超过50 m;当接收器位于海洋中上层时,直达波有效作用范围的季节性变化引起定位性能差异,冬季定位精度优于夏季,两者RMSE相差15～20 m;当接收器位于海洋近底层时,利用可靠声路径定位精度较高,定位性能季节性变化不明显。研究认为,海水的季节性环境变化能够改变半会聚区尺度水面声定位的声信道特性以及到达声信息、误差传播、交会求解等测量因素,进而对接收深度位于海洋上层的声定位性能产生明显影响。     

Track Parameter Estimation from Multipath Delay Information

It is desired to track the location of an underwater acoustic source with range difference measurements from a stationary passive array. Many times, the array has only one or two sensors, and the multipath and intersensor range difference measurements are insufficient to localize and track a source moving along an arbitrary path [1]. Here, we propose to track sources with one- or two-sensur stationary passive arrays by making the simplifying assumption that the source's path can be described by a small set of so-called track parameters. Range difference information can then be used to estimate the track parameter set rather than the source location as a function of time. In this paper, we choose the track parameters to specify a straight-line constant-velocity constant-depth path. Cramer-Rao bounds are presented for estimating these track parameters from the time history of multipath and intersensor range difference measurements. It is shown that this track parameter set cannot be accurately estimated from the time history of a single multipath range difference without side information (an independent velocity estimate, for instance), although multipath and intersensor range difference measurements from a two-sensor array are generally sufficient to estimate the track parameter set. Computationally efficient techniques are presented which estimate track parameters from range difference measurements taken from one- and two-sensor arrays. Monte-Carlo simulations are presented which show that these techniques have sample mean-square error approximately equal to the Cramer-Rao bound when a single multipath range difference and an independent velocity estimate are available. The sample mean-square error is shown to be in the range of two to ten times the corresponding Cramer-Rao bounds when these techniques are applied to two-sensor range difference data.     

基于AIS信息校准的双频地波雷达的船只融合跟踪

高频地波雷达（HFSWR）和自动船只确认系统（AIS）是船只跟踪的重要传感器。高频地波雷达可以用来跟踪探测区域的所有船只,而AIS只能用来确认合作船只的信息。由于海杂波的干扰,使用单频率地波雷达的船只跟踪会淹没在布拉格峰值的盲区里,改变探测频率是克服这一缺点的有效手段。在这种背景下,我们提出一种基于AIS校准的双频雷达融合探测算法。因为不同频率的地波雷达测量与AIS的测量值存在系统误差,所以AIS信息可以用来估计和校准地波雷达的每个频率的系统误差。首先,将合作目标的点迹测量与地波雷达的点迹测量通过JVC分配算法进行点迹关联。从合作船只的点迹关联结果中,双频雷达的系统误差可以估计和校准。其次,基于校准的双频雷达数据,使用融合JPDA-UKF算法进行船只跟踪。通过真实探测的数据的实验结果显示所提算法可以实时跟踪船只,相比单频率跟踪可以进一步提高跟踪能力和跟踪精度。     

Observability of target tracking with range-only measurements

A necessary and sufficient condition for local system observability, a prerequisite to target motion analysis, is presented in this technical communication for two-dimensional manoeuvring target tracking with range-only measurements from a single observer. The approach taken in this paper utilizes the Fisher information matrix developed from the analytical treatment of system dynamics and noisy measurement equations established in a modified polar coordinate system. The analytical results of this paper are demonstrated by a series of simulation studies for applications on naval surface vehicle engagements     

A 1-D search solution for localization from frequency measurements

A source that emits a constant frequency tone and moves at a constant course and speed can be localized through measurements of the Doppler shifted frequencies (DSF). With five unknowns, namely, the rest frequency and the positions and speeds in the x-y directions, five separate sensors would normally be necessary to give five DSP measurements for instantaneous localization. The equations are nonlinear, and the standard solution is by grid search or iteration. The high dimensionality leads to a large computational requirement. By incorporating DSF rates, a quantity available from frequency line trackers, a one-dimensional grid search solution is possible which requires only three sensors and reduces the computational load. The derivation of the grid search technique is given, together with simulation results. The conclusion is that at high signal-to-noise ratios (SNR), the scheme reaches the three-sensor Cramer-Rao lower bound; at lower SNR's or with increased sensors, the grid search answer is a good initializer for a nonlinear optimization algorithm that gives a maximum likelihood estimate     

Target localization and tracking from Doppler-shift measurements

It is possible to localize a nonmaneuvering moving source radiating a constant frequency tone from measurements of the Doppler-shifted frequency at several sensors. Due to the nonlinear nature of the problem, it is necessary to find the solution by grid searches. However, if measurements of the rates of frequency changes are available, the search is only in three dimensions instead of the normal five in source frequency, its x-y positions, and speeds. The validity of combining frequency and frequency-rate measurements is confirmed with simulation studies. The overall system includes a least-squares track-sort algorithm to differentiate the true track from the extraneous track, and a Kalman tracker for the prediction of future source positions, thereby reducing the grid search size. An error analysis relating localization accuracy to uncertainties in frequency measurements and sensor positions is also given     

Multi-Bernoulli Filter for Tracking Multiple Targets Using Sensor Array

This paper presents a multi-Bernoulli filter for tracking the direction of arrival(DOAs) of time-varying number of targets using sensor array. Our method operates directly on the measurements of sensor array and does not require any detection. Firstly, more information is reserved and compared with the after-detection measurements using a finite set of detected points. It can significantly improve the tracking performance, especially in low signal-to-noise ratio. Secondly, it inherits the advantages of the multi-Bernoulli approximation which models each of the targets individually. This allows more accurate multi-target state estimation, especially when targets cross. The proposed filter does not need clustering step and simulation results showcase the improved performance of the proposed filter.     

Multipath channel identification with wavelet packets

This paper deals with the basic modeling problem in underwater acoustics that is the characterization of the channel between a transmitter and a receiver. The problem is analyzed here using an array of sensors that receive PSK signals emitted by several sources. Data come from an experiment realized by a physical system situated in the Mediterranean Sea. In order to identify the multipath channel, we need to access the propagation time delay and the angle of arrival of each propagation ray. However, many of these acoustic ray paths are too close to be separated by classic processing methods (matched filter, beamforming, etc.); new methods with better resolution must be applied in order to analyze the experimental signals and to determine their arrival time on the array of sensors. After a presentation of this problem, we will first discuss high-resolution methods that are usually applied in the localization problem; we will then focus on wavelet packet analysis which provides good results by improving the temporal resolution of acoustic signals     

Robust ROV path following considering disturbance and measurement error using data fusion

ROV accurate path following is challenging due to system unmodeled dynamics, disturbances and navigation sensors error. The model uncertainty and disturbances are commonly treated using robust methods such as the sliding mode controller where by incorporating an integral action in the zero tracking error is also guaranteed. Practically, the ROV position data is often computed using low cost inertial measurement unit (IMU) with outputs contaminated with bias and noise. Failure of mission is an immediate consequence of employing such biased sensors. However, the problem can be circumvented using the concept of redundant measurements and data fusion. In this respect, a set of 12 measurements from IMU, magnetometer and Doppler velocity log (DVL) are employed where the last two are aided sensors. The set up is shown to be capable of providing ROV path following with zero (in average) steady state tracking error irrespective of its dynamic parameters, environmental disturbances and erroneous data; as if it enjoys the exact values of the position of the ROV. It means that the combined DVL and magnetometer are sufficient for filtering the IMU biased measurements. Various simulations conducted confirm the results.     

基于小型三维阵列的瞬态声源快速被动定位方法

重物在落水和着底过程中都会产生瞬态声信号,这类信号可被运用于浅水区域水下目标定位。 针对浅水区域目标定位的问题,提出了一种基于小型立体五元基阵的瞬态声源快速被动定位算法。 在分析重物落水信号特征的基础上,选取合适的广义互相关加权函数求得传声器之间的声程差,运用快速最小二乘搜索算法进行声源定位。 结果表明:运用 5 传声器阵列可以同时兼顾定位精度和鲁棒性,且满足实时性要求,该方法可运用于浅水区域瞬态声源定位等领域。     

Methods of array element localization for a towed underwateracoustic array

The location of the hydrophones on a towed underwater acoustic array as a function of time (array element localization) is needed for signal processing. Methods to perform this localization using least squares polynomial fitting to data from depth sensors, heading sensors, and sensors detecting a ping from a single source are discussed. Arc distance along the array is used as the independent parameter so that all solutions are constrained to be space curves. Examples of application to real data are presented, and techniques to discriminate against bad sensor data are discussed     

Experimental Evaluation of Tracking Algorithms Used for the Determination of Fish Behavioral Statistics

The fine-scale swimming behavior of fish can now be studied because of the development of sophisticated measurement devices such as multibeam sonar and stereo video systems. However, even with these sensors, improved methods are still required to generate quality estimates of swimming speeds and turn rates. Biologists have commonly relied on pointwise differentiation of noisy position measurements while engineers have focused on Bayesian algorithms to track underwater vehicles. A comparative evaluation of the performance of these tracking algorithms for the analysis of fine-scale behavior of fish was performed using a data set of 100 fish tracks recorded simultaneously with a multibeam sonar and a stereo video camera system. The segmenting track identifier, a non-Bayesian curve fitting and segmenting tracker, is shown to be most effective for tracking the unpredictable and complex horizontal motion of fish while a Kalman smoother using a constant-velocity model is shown to be most effective for tracking the more predictable and piecewise linear vertical motion of fish. Both are shown to be more effective than pointwise differentiation. Criteria for selecting an appropriate algorithm for a given motion study are provided     

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.     

Acoustic positioning for an array of freely drifting infrasonic sensors

Initial testing of the prototype element of a freely drifting infrasonic sensor array is described. The intent of this measurement system is to gather wide aperture data sets which will be used both to characterize ambient noise in the region 1-10 Hz and to assess the gains possible from beam forming utilizing a collection of very low frequency (VLF) sensors. Coherent processing (beam forming) of the infrasonic sensor data is made possible by relative position measurements derived from mutual acoustic interrogation of the elements at a higher frequency. Surface echo data from a recent sea test of the prototype buoy are used to illustrate the type of pulse processing which will be implemented as a first step in the localization procedure.     

西沙北部海域海洋环境噪声频谱特性

Ambient noise is very important in the prediction system of a sonar performance, because it determines the detection ranges always in a passive sonar and usually in an active sonar. In the uncertainty issue for the so-nar performance, it is necessary to know this factor＇s statistical characteristics that are only obtained by data processing from the underwater ambient noise measurements. Broad-band ambient noise signals from 16 hydrophones were amplified and recorded for 2 min every 1 h. The results show that the ambient noise is essentially depth independent. The cross correlation of the ambient noise levels （1, 6 and 12 h average） with a wind speed is presented. It was found that the correlation is excellent on the upper frequency band and the noise levels correlate better with high wind speed than with low wind speed.     

A comparison of sea-state parameters from nautical radar images and buoy data

Nautical radar and scalar buoy measurements of ocean wind generated waves have been analysed to compare the spectral parameters estimated from both sensors. The time series of different sea-state parameters and the differences and ratios of the values obtained from radar and buoy data using different analysis methods are compared. It has been observed that main differences between the sea-state parameters derived by using measurements obtained from both sensors result both from device characteristics and from the method of spectral estimation. In particular, it is shown that the Nyquist frequency has an important effect on the value of the sea-state parameters depending on spectral moments of order higher than zero.     

Joint direction-of-arrival and array-shape tracking for multiplemoving targets

The problem of tracking the directions-of-arrival (DOAs) of multiple moving sonar targets with an array of passive sensors is complicated by sensor movement. An algorithm for the joint tracking of source DOAs and sensor positions is presented to address this problem. Initial maximum-likelihood estimates of source DOAs and sensor positions are refined by Kalman filtering. Spatio-temporally correlated array movement is considered. Source angle dynamics are used to achieve correct data association. The new technique is capable of performing well for the difficult cases of sources that cross in angle as well as for fully coherent sources. Computer simulations show that the approach is robust in the presence of array motion modeling uncertainty and effectively reduces dependence on expensive and possibly unreliable hardware     

一种基于伽利略搜救系统的联合定位算法

分析了伽利略搜救系统的地面站定位模型。提出了一种适用于该系统的,在存在多余观测的情况下,基于信号的时间延迟和多普勒频率测量值加权后,共同参与平差计算的联合定位算法模型及其误差分布模型。仿真结果表明,与单纯使用一种观测值的定位算法相比,该算法可以提高定位精度,是一种适合伽利略搜救地面站使用的定位算法。