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Multiple model efficient particle filter based track-before-detect for maneuvering weak targets 被引量:9
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作者 BAO Zhichao JIANG Qiuxi LIU Fangzheng 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2020年第4期647-656,共10页
It is a tough problem to jointly detect and track a weak target, and it becomes even more challenging when the target is maneuvering. The above problem is formulated by using the Bayesian theory and a multiple model(M... It is a tough problem to jointly detect and track a weak target, and it becomes even more challenging when the target is maneuvering. The above problem is formulated by using the Bayesian theory and a multiple model(MM) based filter is proposed. The filter presented uses the MM method to accommodate the multiple motions that a maneuvering target may travel under by adding a random variable representing the motion model to the target state. To strengthen the efficiency performance of the filter,the target existence variable is separated from the target state and the existence probability is calculated in a more efficient way. To examine the performance of the MM based approach, a typical track-before-detect(TBD) scenario with a maneuvering target is used for simulations. The simulation results indicate that the MM based filter proposed has a good performance in joint detecting and tracking of a weak and maneuvering target, and it is more efficient than the general MM method. 展开更多
关键词 particle filter track-before-detect(TBD) maneuvering target tracking multiple model(MM)
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Bayesian track-before-detect algorithm for nonstationary sea clutter 被引量:2
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作者 XU Cong HE Zishu +1 位作者 LIU Haicheng LI Yadan 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2021年第6期1338-1344,共7页
Radar detection of small targets in sea clutter is a particularly demanding task because of the nonstationary characteristic of sea clutter.The track-before-detect(TBD)filter is an effective way to increase the signal... Radar detection of small targets in sea clutter is a particularly demanding task because of the nonstationary characteristic of sea clutter.The track-before-detect(TBD)filter is an effective way to increase the signal-to-clutter ratio(SCR),thus improving the detection performance of small targets in sea clutter.To cope with the nonstationary characteristic of sea clutter,an easily-implemented Bayesian TBD filter with adaptive detection threshold is proposed and a new parameter estimation method is devised which is integrated into the detection process.The detection threshold is set according to the parameter estimation result under the framework of information theory.For detection of closely spaced targets,those within the same range cell as the one under test are treated as contribution to sea clutter,and a successive elimination method is adopted to detect them.Simulation results prove the effectiveness of the proposed algorithm in detecting small targets in nonstationary sea clutter,especially closely spaced ones. 展开更多
关键词 small target track-before-detect(TBD) nonstationary sea clutter closely spaced target
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SMC-PHD based multi-target track-before-detect with nonstandard point observations model 被引量:5
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作者 占荣辉 高彦钊 +1 位作者 胡杰民 张军 《Journal of Central South University》 SCIE EI CAS CSCD 2015年第1期232-240,共9页
Detection and tracking of multi-target with unknown and varying number is a challenging issue, especially under the condition of low signal-to-noise ratio(SNR). A modified multi-target track-before-detect(TBD) method ... Detection and tracking of multi-target with unknown and varying number is a challenging issue, especially under the condition of low signal-to-noise ratio(SNR). A modified multi-target track-before-detect(TBD) method was proposed to tackle this issue using a nonstandard point observation model. The method was developed from sequential Monte Carlo(SMC)-based probability hypothesis density(PHD) filter, and it was implemented by modifying the original calculation in update weights of the particles and by adopting an adaptive particle sampling strategy. To efficiently execute the SMC-PHD based TBD method, a fast implementation approach was also presented by partitioning the particles into multiple subsets according to their position coordinates in 2D resolution cells of the sensor. Simulation results show the effectiveness of the proposed method for time-varying multi-target tracking using raw observation data. 展开更多
关键词 adaptive particle sampling multi-target track-before-detect probability hypothesis density(PHD) filter sequential Monte Carlo(SMC) method
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Maneuvering target track-before-detect via multiple-model Bernoulli particle filter
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作者 占荣辉 刘盛启 +1 位作者 胡杰民 张军 《Journal of Central South University》 SCIE EI CAS CSCD 2015年第10期3935-3945,共11页
Target tracking using non-threshold raw data with low signal-to-noise ratio is a very difficult task, and the model uncertainty introduced by target's maneuver makes it even more challenging. In this work, a multi... Target tracking using non-threshold raw data with low signal-to-noise ratio is a very difficult task, and the model uncertainty introduced by target's maneuver makes it even more challenging. In this work, a multiple-model based method was proposed to tackle such issues. The method was developed in the framework of Bernoulli filter by integrating the model probability parameter and implemented via sequential Monte Carlo(particle) technique. Target detection was accomplished through the estimation of target's existence probability, and the estimate of target state was obtained by combining the outputs of modeldependent filtering. The simulation results show that the proposed method performs better than the TBD method implemented by the conventional multiple-model particle filter. 展开更多
关键词 Bernoulli filter multiple model target maneuver track-before-detect(TBD) sequential Monte Carlo(SMC) technique
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Track-before-detect for bistatic radar based on pseudo-spectrum
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作者 Tao HAN Gongjian ZHOU 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2024年第1期236-246,共11页
Track-Before-Detect(TBD) is an efficient method to detect dim targets for radars. Conventional TBD usually follows an approximate motion model of the target, which may cause an inaccurate integration of the target ene... Track-Before-Detect(TBD) is an efficient method to detect dim targets for radars. Conventional TBD usually follows an approximate motion model of the target, which may cause an inaccurate integration of the target energy. A TBD technique on basis of pseudo-spectrum in mixed coordinates adopting an accurate motion model for bistatic radar system is developed in this paper.The predicted position in bistatic polar plane is derived according to a nonlinear function that exactly describes the constant Cartesian velocity motion. Then around the predicted position, a pseudo-spectrum is formulated and its samples are accumulated to the integration frame for energy integration. The evolution of the state and the procedure of accumulation of the target energy are derived elaborately. The superior performance of the proposed method is demonstrated by some simulations. 展开更多
关键词 Weak target detection Bistatic radar track-before-detect Pseudo-spectrum Multiframe integration
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Track-before-detect for Infrared Maneuvering Dim Multi-target via MM-PHD 被引量:19
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作者 LONG Yunli XU Hui +1 位作者 AN Wei LIU Li 《Chinese Journal of Aeronautics》 SCIE EI CSCD 2012年第2期252-261,共10页
In this paper, we present a novel and efficient track-before-detect (TBD) algorithm based on multiple-model probability hypothesis density (MM-PHD) for tracking infrared maneuvering dim multi-target. Firstly, the ... In this paper, we present a novel and efficient track-before-detect (TBD) algorithm based on multiple-model probability hypothesis density (MM-PHD) for tracking infrared maneuvering dim multi-target. Firstly, the standard sequential Monte Carlo probability hypothesis density (SMC-PHD) TBD-based algorithm is introduced and sequentially improved by the adaptive process noise and the importance re-sampling on particle likelihood, which result in the improvement in the algorithm robustness and convergence speed. Secondly, backward recursion of SMC-PHD is derived in order to ameliorate the tracking performance especially at the time of the multi-target arising. Finally, SMC-PHD is extended with multiple-model to track maneuvering dim multi-target. Extensive experiments have proved the efficiency of the presented algorithm in tracking infrared maneuvering dim multi-target, which produces better performance in track detection and tracking than other TBD-based algorithms including SMC-PHD, multiple-model particle filter (MM-PF), histogram probability multi-hypothesis tracking (H-PMHT) and Viterbi-like. 展开更多
关键词 target tracking probability hypothesis density Monte Carlo track-before-detect importance re-sampling
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Multiple model particle flter track-before-detect for range ambiguous radar 被引量:16
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作者 Wang Guohong Tan Shuncheng +2 位作者 Guan Chengbin Wang Na Liu Zhaolei 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2013年第6期1477-1487,共11页
The middle pulse repetition frequency(MPRF)and high pulse repetition frequency(HPRF)modes are widely adopted in airborne pulse Doppler(PD)radar systems,which results in the problem that the range measurement of ... The middle pulse repetition frequency(MPRF)and high pulse repetition frequency(HPRF)modes are widely adopted in airborne pulse Doppler(PD)radar systems,which results in the problem that the range measurement of targets is ambiguous.The existing data processing based range ambiguity resolving methods work well on the condition that the signal-to-noise ratio(SNR)is high enough.In this paper,a multiple model particle flter(MMPF)based track-beforedetect(TBD)method is proposed to address the problem of target detection and tracking with range ambiguous radar in low-SNR environment.By introducing a discrete variable that denotes whether a target is present or not and the discrete pulse interval number(PIN)as components of the target state vector,and modeling the incremental variable of the PIN as a three-state Markov chain,the proposed algorithm converts the problem of range ambiguity resolving into a hybrid state fltering problem.At last,the hybrid fltering problem is implemented by a MMPF-based TBD method in the Bayesian framework.Simulation results demonstrate that the proposed Bayesian approach can estimate target state as well as the PIN simultaneously,and succeeds in detecting and tracking weak targets with the range ambiguous radar.Simulation results also show that the performance of the proposed method is superior to that of the multiple hypothesis(MH)method in low-SNR environment. 展开更多
关键词 Bayesian framework Particle flter Pulse repetition frequency Range ambiguity Signal-to-noise ratio track-before-detect
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Multiframe weak target track-before-detect based on pseudo-spectrum in mixed coordinates 被引量:1
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作者 Liangliang WANG Gongjian ZHOU Thiagalingam KIRUBARAJAN 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2022年第5期97-113,共17页
Traditional multiframe Track-Before-Detect(TBD)may incur adverse integration loss resulting from model mismatch in sensor coordinates.Its suboptimal integration strategy may cause target envelope degradation.To addres... Traditional multiframe Track-Before-Detect(TBD)may incur adverse integration loss resulting from model mismatch in sensor coordinates.Its suboptimal integration strategy may cause target envelope degradation.To address these issues,a pseudo-spectrum-based multiframe TBD in mixed coordinates is proposed firstly.The data search for energy integration is conducted based on an accurate model in the x-y plane while target energy is integrated based on pseudo-spectrum in sensor coordinates.The algorithm performance is improved since the model mismatch is eliminated,and the pseudo-spectrum based integration facilitates well maintained target envelope.The detailed multiframe integration procedure and theoretical target integrated envelope are derived.Secondly,to cope with the unknown target velocity,a velocity filter bank based on pseudo-spectrum in mixed coordinates is proposed.The effect of velocity mismatch on algorithm performance is analyzed and an efficient method for filter bank design is presented.Thirdly,a parameter estimation method using characteristics of integrated envelope is presented for improved target polar position and Cartesian velocity estimation.Finally,numerical results are provided to demonstrate the effectiveness of the proposed method. 展开更多
关键词 Mixed coordinates Multiframe detection Pseudo-spectrum track-before-detect Weak target detection
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A multi-frame track-before-detect algorithm based on root label clustering for multiple targets
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作者 Jiaqi ZHANG Haihong TAO +1 位作者 Xiushe ZHANG Chunlei HAN 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2022年第5期87-96,共10页
In this paper,a novel multi-frame track-before-detect algorithm is proposed,which is based on root label clustering to reduce the high computational complexity arising by observation area expansion and clutter/noise d... In this paper,a novel multi-frame track-before-detect algorithm is proposed,which is based on root label clustering to reduce the high computational complexity arising by observation area expansion and clutter/noise density increase.A criterion of track extrapolation is used to construct state transition set,root label is marked by state transition set to obtain the distribution information of multiple targets in measurement space,then measurement plots of multi-frame are divided into several clusters,and finally multi-frame track-before-detect algorithm is implemented in each cluster.The computational complexity can be reduced by employing the proposed algorithm.Simulation results show that the proposed algorithm can accurately detect multiple targets in close proximity and reduce the number of false tracks. 展开更多
关键词 Multi-frame track-before-detect Multiple targets detection Root label clustering State transition set Track extrapolation
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Multi-Bernoulli Filter for Tracking Multiple Targets Using Sensor Array 被引量:1
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作者 ZHANG Guang-pu ZHENG Ce +1 位作者 QIU Long-hao SUN Si-bo 《China Ocean Engineering》 SCIE EI CSCD 2020年第2期245-256,共12页
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 no... 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. 展开更多
关键词 multiple target tracking multi-Bernoulli filter direction of arrival estimation random finite set track-before-detect
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A novel RHT-TBD approach for weak targets in HPRF radar 被引量:6
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作者 Hongbo YU Guohong WANG +1 位作者 Wei WU Shuncheng TAN 《Science China Earth Sciences》 SCIE EI CAS CSCD 2016年第12期59-72,共14页
A novel approach, which can handle ambiguous data from weak targets, is proposed within the randomized Hough transform track-before-detect(RHT-TBD) framework. The main idea is that, without the pre-detection and ambig... A novel approach, which can handle ambiguous data from weak targets, is proposed within the randomized Hough transform track-before-detect(RHT-TBD) framework. The main idea is that, without the pre-detection and ambiguity resolution step at each time step, the ambiguous measurements are mapped by the multiple hypothesis ranging(MHR) procedure. In this way, all the information, based on the relativity in time and pulse repetition frequency(PRF) domains, can be gathered among different PRFs and integrated over time via a batch procedure. The final step is to perform the RHT with all the extended measurements, and the ambiguous data is unfolded while the detection decision is confirmed at the end of the processing chain.Unlike classic methods, the new approach resolves the problem of range ambiguity and detects the true track for targets. Finally, its application is illustrated to analyze and compare the performance between the proposed approach and the existing approach. Simulation results exhibit the effectiveness of this approach. 展开更多
关键词 high pulse repetition frequency weak targets track-before-detect randomized Hough transform multiple hypothesis ranging range ambiguity resolution
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