Performance evaluation for multi-target tracking with temporal dimension specifics

With the great development of Multi-Target Tracking(MTT) technologies,many MTT algorithms have been proposed with their own advantages and disadvantages.Due to the fact that requirements to MTT algorithms vary from the application scenarios,performance evaluation is significant to select an appropriate MTT algorithm for the specific application scenario.In this paper,we propose a performance evaluation method on the sets of trajectories with temporal dimension specifics to compare the estimated trajectories with the true trajectories.The proposed method evaluates the estimate results of an MTT algorithm in terms of tracking accuracy,continuity and clarity.Furthermore,its computation is based on a multi-dimensional assignment problem,which is formulated as a computable form using linear programming.To enhance the influence of recent estimated states of the trajectories in the evaluation,an attention function is used to reweight the trajectory errors at different time steps.Finally,simulation results show that the proposed performance evaluation method is able to evaluate many aspects of the MTT algorithms.These evaluations are worthy for selecting suitable MTT algorithms in different application scenarios.     

Improved multi-target tracking in clutter by PDA smoothing

An algorithm is presented for the recursive tracking of multiple targets in cluttered environment by making use of the joint probabilistic data association fixed-lag smoothing (JPDAS) techniques. It is shown that a significant improvement in the accuracy of track estimation of both nonmaneuvering and maneuvering targets may be achieved by introducing a time lag of one or two sampling periods between the instants of estimation and latest measurement. Results of simulation experiments for a radar tracking problem that demonstrate the effects of fixed-lag smoothing are also presented     

A novel variable-lag probability hypothesis density smoother for multi-target tracking

It is understood that the forward-backward probability hypothesis density (PHD) smoothing algorithms proposed recently can significantly improve state estimation of targets. However, our analyses in this paper show that they cannot give a good cardinality (i.e., the number of targets) estimate. This is because backward smoothing ignores the effect of temporary track drop- ping caused by forward filtering and/or anomalous smoothing resulted from deaths of targets. To cope with such a problem, a novel PHD smoothing algorithm, called the variable-lag PHD smoother, in which a detection process used to identify whether the filtered cardinality varies within the smooth lag is added before backward smoothing, is developed here. The analytical results show that the proposed smoother can almost eliminate the influences of temporary track dropping and anomalous smoothing, while both the cardinality and the state estimations can significantly be improved. Simulation results on two multi-target tracking scenarios verify the effectiveness of the proposed smoother.     

A robust Poisson multi-Bernoulli filter for multi-target tracking based on arithmetic average fusion

The coalescence and missed detection are two key challenges in Multi-Target Tracking (MTT). To balance the tracking accuracy and real-time performance, the existing Random Finite Set (RFS) based filters are generally difficult to handle the above problems simultaneously, such as the Track-Oriented marginal Multi-Bernoulli/Poisson (TOMB/P) and Measurement-Oriented marginal Multi-Bernoulli/Poisson (MOMB/P) filters. Based on the Arithmetic Average (AA) fusion rule, this paper proposes a novel fusion framework for the Poisson Multi-Bernoulli (PMB) filter, which integrates both the advantages of the TOMB/P filter in dealing with missed detection and the advantages of the MOMB/P filter in dealing with coalescence. In order to fuse the different PMB distributions, the Bernoulli components in different Multi-Bernoulli (MB) distributions are associated with each other by Kullback-Leibler Divergence (KLD) minimization. Moreover, an adaptive AA fusion rule is designed on the basis of the exponential fusion weights, which utilizes the TOMB/P and MOMB/P updates to solve these difficulties in MTT. Finally, by comparing with the TOMB/P and MOMB/P filters, the performance of the proposed filter in terms of accuracy and efficiency is demonstrated in three challenging scenarios.     

Adapitive waveform design for distributed OFDM MIMO radar system in multi-target scenario

In order to improve detection and estimation performance of distributed Orthogonal-Frequency-Division Multiplexing (OFDM) Multiple-Input Multiple-Output (MIMO) radar system in multi-target scene, we propose a novel approach of Adaptive Waveform Design (AWD) based on a constrained Multi-Objective Optimization (MOO). The sparse measurement model of this radar system is derived, and the method based on decomposed Dantzig selectors is applied for the sparse recovery according to the block structures of the sparse vector and the system matrix. An AWD approach is proposed, which optimizes two objective functions, namely minimizing the upper bound of the recovery error and maximizing the weakest-target return, by adjusting the complex weights of the emitting waveform amplitudes. Several numerical simulations are provided and their results show that the detection and estimation performance of the radar system is improved significantly when this MOO-based AWD approach is applied to the distributed OFDM MIMO radar system. Especially, we verify the effectiveness of our AWD approach when the available samples are reduced severally and the technique of compressed sensing is introduced.     

Design and analysis of a regulated peak-power tracking system

A regulated peak-power tracking (RPPT) system for space power application is proposed. Large-signal stability analysis is provided to understand the main four different modes of operations of the system, as well as the mode transitions. A simple and effective control scheme for the system is also proposed. Small-signal analysis is performed thereafter to provide design optimization, and the predictions are verified by computer simulations     

Design of tracking system of telemetering antenna in pilotlessaircraft

In this paper, the design plan of the tracking system of the telemetering antenna in a type of pilotless aircraft is introduced. The discussion centres on the controls. Then the format of control words and an algorithm, which are effectively used to control the stepping motor are given. This algorithm has a function of parallel control and has already been used in our research. The design of the antenna servo system and the fining step pitch (FSP) control of the stepping motor will benefit from this paper     

Improved CFAR performance in the littoral

Littoral operation of radars poses severe signal processing difficulties due to the highly stressing, inhomogeneous clutter. This report describes an initial investigation into the feasibility of utilising site-specific radar modelling to provide a localised estimate of the clutter statistics which can then be used to predict the required threshold to maintain a given false alarm rate. The technique has been applied to littoral clutter recordings obtained from the experimental S-band phased array radar, MESAR2. Results are presented for the technique in comparison with a conventional, non-adaptive, cell averaging CFAR. This paper concludes that significant performance enhancements are possible through the use of this new technique.     

Rank detector preprocessor for glint reduction in a tracking radar

A rank detector is used to detect instantaneous received power fades in a tracking radar. On detection of a fade, censorship of the angular position measurement is implemented in a Kalman tracking filter. It is shown that this technique can typically give a 15% angular tracking improvement on highly dynamic targets     

Passive tracking scheme for a single stationary observer

While there are many techniques for bearings-only tracking (BOT) in the ocean environment, they do not apply directly to the land situation. Generally, for tactical reasons, the land observer platform is stationary; but, it has two sensors, visible and infrared, for measuring bearings and a laser range finder (LRF) for measuring range. There is a requirement to develop a new BOT data fusion scheme that fuses the two sets of bearing readings, and together with a single LRF measurement, produces a unique track. This paper first develops a parameterized solution for the target speeds, and then heading, prior to the occurrence of the LRF measurement, when the track is unobservable. At, and after the LRF measurement, a BOT, formulated as a least squares (LS) estimator, then produces a unique LS estimate of the target states. Bearing readings from the other sensor serve as instrumental variables in a data fusion setting to eliminate the bias in the BOT estimator. The result is an unbiased and decentralized data fusion scheme. Results from two simulation experiments have corroborated the theoretical development and show also that the scheme is optimal.     

Information type filters for tracking a maneuvering target

Two previously proposed adaptive covariance-type Kalman filtering techniques for tracking maneuvering targets (see Y.T. Chan et al. ibid., p.237-44, Mar. 1979, and Z. Tang et al. Report, Department of Electrical and Computer Engineering, Oregon State University, Corvallis, Oct. 1983) are developed further to utilize the information-type Kalman filter. These adaptive information-type filters are described in structurally decoupled forms, thereby greatly reducing the computational requirements while rendering the filters amenable to implementation on parallel processors. A coherent decision procedure for including partial coupling when necessary is developed via offline analysis of crosscorrelation functions     

Design considerations for a real-time random-noise tracking radar

Random-noise radar has been applied successfully to range measurement, velocity estimation and terrain/target imaging. For applications involving stationary targets, long integration times and process averaging are easily tolerated. In situations where the target or radar platform moves at high speed, the impact of this relative motion on system design should be considered. This work addresses the statistical performance of a generic random-noise radar receiver and examines the inter-relationships between design parameters and performance tradeoffs. Complementing this examination, a random-noise monopulse system is also investigated as a possible architecture for real-time angle estimation. Simulations and numerical illustrations provide the basis of processor design and performance prediction.     

A target cueing and tracking system (TCATS) for smart videoprocessing

A smart system that uses state-of-the-art image processing techniques to detect and track targets moving in video or infrared imagery is presented. It is a general-purpose system that was developed to be independent of the application and the user interface. TCATS has successfully demonstrated a high detection capability and the ability to ignore exterior environmental conditions, such as cloud shadows moving through the scene, snow, blowing dust, rain and moderate camera motion. TCATS can handle many targets and retain the identity of each object from one frame to the next. Special rugged hardware has been developed to reduce the size, cost, and power consumption and to increase the processing rate, reliability, and environmental operating capability of the system. TCATS can be incorporated into an existing video assessment system without a major cost outlay intruder. The TCATS algorithms, custom-developed hardware, and preliminary field test results are described     

A new high performance multipurpose satellite tracking system

The European Space Agency's (ESA) multipurpose satellite tracking system is introduced. The system is able to perform accurate satellite ranging and Doppler measurements for a variety of mission types, i.e., from near-Earth satellites to deep space probes. The ranging signal is analyzed and described in an analytical manner from which the limits of the system performance are derived. A model of the overall system is presented and a few simulation results obtained thereby are compared with measurements performed with the ESA's Giotto and Hipparcos scientific missions     

Event-triggered and consensus-based attitude tracking alignment for discrete-time multiple spacecraft system exploiting interference

This paper presents a discrete-time attitude control strategy with equi-global practical stabilizability for aligning the attitude of multiple spacecraft to a predesigned configuration according to a time-variant reference. By utilizing the interference of the wireless channel, the communication scheme designed in this paper can save communication resources, amount of computation, and energy proportionally to the number of spacecraft. The exact discrete-time model and approximate discrete-time model of the consensus-based spacecraft tracking system are given. Then the framework for the design of an event-triggered control scheme for the exact discrete-time system via its approximate models is developed, which avoids the periodic actuation, and Zeno behavior is proved to be excluded. Furthermore, the control scheme can handle the presence of the unknown fading channel. Finally, simulation results are presented to demonstrate the effectiveness of the control strategy.     

A multisensor tracking system with an image-based maneuver detector

Rapid and reliable decisions about the onset and termination of maneuvers are critical for accurate tracking of maneuvering targets. Given the appropriate filter model, the use of multiple sensors of different capabilities and strengths can improve the quality and the reliability of the tracking system A multisensor tracking system where the usage of the image sensor is two fold is presented. First, if is used to perform maneuver detection using minimum computation and storage. Second, its bearing and elevation measurements are used along with 3-D radar observations to improve the tracking quality. The advantages of the proposed multisensor tracking system are discussed and demonstrated via simulations     

基于知识的精铸模具智能化设计方法

在原有标准件建库工具的基础上,引入知识工程,结合特征技术,介绍了模具知识分类及其表示方法,并提出了合理的推理机制,使系统智能生成用户所需模具。建立了基于知识的精铸模具智能生成系统,提高了设计质量和效率。     

Engineering in a virtual environment

The authors review virtual environment technology and its application to the aerospace industry. Virtual environment systems have three components: sensors, effectors, and interlinkage hardware and software. Virtual environment tools used by the aerospace industry include the Multi-dimensional, User-oriented, Synthetic Environment (MUSE); Cave Automatic Virtual Environment (CAVE); and Immersadesk. Engineering applications include design and manufacture of aerospace systems, maintenance, and repair.     

Radar modelling to improve CFAR performance in the littoral

Littoral operation of radars poses severe signal processing difficulties due to the highly stressing, inhomogeneous clutter. This report describes an initial investigation into the feasibility of utilising site specific radar modelling to provide a localized estimate of the clutter statistics which can then be used to predict the required threshold to maintain a given false alarm rate. The technique has been applied to littoral clutter recordings obtained from the experimental S-band phase array radar, MESAR2. Results are presented for the technique in comparison with a conventional, non-adaptive, cell averaging CFAR. The paper concludes that significant performance enhancements are possible through the use of this new technique.     

多飞行器动态目标追踪协同控制研究

多飞行器追踪动态目标是一个协同控制问题,需要根据目标飞行状态,协同各个追踪飞行器的飞行状态,最终能够在某动态的最佳点实现同时到达。考虑到目标具有较强的机动性,轨迹通常为非线性的,设计了一种基于非线性轨迹预测的、以剩余时间为控制变量的一致性控制方案。仿真结果表明,提出的控制方案能够实现空间位置相距较远的多飞行器动态追踪,具有较好的灵活性和收敛性,目标轨迹的预测结果与实际轨迹误差较小,恰当的轨迹估计有助于缩短追踪时间,提高追踪效率。