微弱目标检测前跟踪算法研究
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摘要
随着隐身技术的发展与广泛应用，典型军事目标如战斗机、导弹和巡洋舰的雷达截面积（RCS）锐减，导致回波信号微弱，给雷达的检测与跟踪带来了极大的挑战。传统的先检测后跟踪（DBT）技术很难保证此类微弱目标的可靠检测和跟踪，检测前跟踪（TBD）技术在不改变现有雷达系统的前提下，通过联合处理多帧原始数据积累能量，实现对目标的检测并恢复航迹，是微弱目标检测和跟踪的有效方法之一。TBD技术作为一项正在发展中的新技术，研究其在雷达系统中的相关理论、改进相应的算法、拓展应用背景，进一步提高对微弱目标的检测与跟踪性能显得非常迫切。
本论文围绕雷达系统中的微弱目标检测前跟踪算法，开展了如下工作：
1.分析比较了先检测后跟踪技术和检测前跟踪技术的异同和优缺点，根据多帧之间能量积累方式的不同，将检测前跟踪技术分类为多帧之间非相参积累和多帧之间相参积累的方式，分别给出了两种不同方式下信号处理的流程以及相应的算法，为本文后面章节的研究奠定了基础。
2.提出了一种改进的极坐标随机Hough变换TBD算法，给出了选择最大采样次数的准则，利用帧与帧之间目标的运动信息抑制了大量的无效采样，采用最小距离投票准则克服了投票时的峰值展宽问题，所提算法的检测跟踪性能均优于传统的极坐标随机Hough变换TBD算法。
3.提出了一种距离扩展目标粒子滤波TBD算法。建立了距离扩展目标运动模型和多散射点的量测模型，提出了一种距离扩展目标粒子滤波TBD算法，实现了对距离扩展目标有无、运动状态和长度的同时估计，与最新的B-PF-TBD算法相比，检测和跟踪性能更高。
4.提出了自适应马尔可夫链蒙特卡洛（MCMC）采样的粒子滤波TBD多目标算法，通过自适应采样策略，对相互临近的目标联合采样，对彼此远离的目标逐一的独立采样，提高了算法的运算效率，与马尔可夫链蒙特卡洛粒子滤波TBD多目标算法相比，收敛速度更快；与基于重要性重采样的粒子滤波TBD多目标算法相比，跟踪精度更高。
5.提出了多帧相参积累TBD算法。通过对运动目标回波的分析，建立了多帧相参积累TBD算法的信号模型，基于该信号模型，推导了GLRT检测器，提出了一种高效的多帧相参积累TBD算法来估计目标的未知参数（目标所在的方位单元、距离单元、多普勒频率和调频斜率），实现了对多帧时间内目标回波的相参积累。推导了基于多帧相参积累TBD算法的GLRT检测器的检测概率和虚警概率的解析表达式，从理论上分析了算法的检测性能。最后采用仿真实验验证了信号模型的正确性和多帧相参积累TBD算法的有效性。
With the development and wide utilization of stealthy technology, the radar crosssection (RCS) of typical military targets, such as aircrafts, missels and combat ships,has been greatly decreased. The reflected signal from these targets is very weak causingsevere challenges to radar detection and tracking. The traditional Detect-Before-Track(DBT) methods cannot guarantee reliable detection and tracking performance whenencounted with these weak targets. Track-Before-Detect (TBD) methods are one of theeffective methods of detection and tracking weak targets, which jointly process severalconsecutive scans of unthresholded data to integrate the targets energy, jointly declearthe presence of the targets, and, enentually, its track. As a developing new technique,it’s urgent to investigate TBD theories, modifiy TBD methodologies and expend TBDapplication for weak targets in radar system which can improve detection and trackingperformances.
In this dissertation, TBD algorithm for weak targets in radar system is investigated.The main results are as follows:
1. The differences and the advantages and disadvantages of DBT methods andTBD methods are analysised and comparisoned. And TBD methods are classified ascoherent accumulation and non-coherent accumulation among the frames by the way ofenergy accumulation. The signal processing process and algorithms of the two ways arepresented, respectively. This chapter makes the theoretical foundation of the subsequentchapters of this thesis.
2. A modified polar random Hough transform based TBD algorithm (MP-RHT-TBD) is proposed. The criterion of maximum sampling number is presented. Thetargets’ motion information among frames is utilized to restrain the amount of invalidsampling, and the rule of voting by minimum distance overcomes the problem of peakbroadening. The MP-RHT-TBD algorithm has better detection and trackingperformaces than the P-RHT-TBD algorithm.
3. A particle filter based TBD algorithm for range extent targets is proposed. Themotion model and measurement model of multi-scatterers for range extent targets are built. A particle filter based TBD algorithm for range extent targets is proposed toestimate the presence/absence, the motion states and length of the range extent targets,simultaneously. By comparison with the existing TBD algorithm for extent targets, theproposed algorithm has better performance of the detection and tracking.
4. A novel PF-TBD based on adaptive Markov Chain Monte Carlo (MCMC) formulti-targets is proposed. By the adaptive sampling strategy, adjacent targets are jointsampled and far-away targets are independent sampled. This adaptive samplingimproves efficiency of algorithm and has better rate of convergence than MCMC-PF-TBD algorithm, and has better tracking precision than the SIR-PF-TBD algorithm.
5. A multi-frame coherent TBD technology is proposed. By the analysis of theechoes of the moving targets, a signal model for coherent accumulation among frames isbuilt. Based on the model, the GLRT detector is derived, and an efficient coherentaccumulation algorithm is proposed to estimate the unknown parameters of the target(targets’ azimuth, distance, Doppler and modulation slope). The analytical expressionsof false alarm and detection probabilitiy of GLRT detector based on the proposedalgorithm are derived, and the performance of detection of the algorithm is analyzedtheoretically. Finally, the validity of the signal model and the efficiency of the proposedalgorithm are verified by simulation experiments.
本论文围绕雷达系统中的微弱目标检测前跟踪算法，开展了如下工作：
1.分析比较了先检测后跟踪技术和检测前跟踪技术的异同和优缺点，根据多帧之间能量积累方式的不同，将检测前跟踪技术分类为多帧之间非相参积累和多帧之间相参积累的方式，分别给出了两种不同方式下信号处理的流程以及相应的算法，为本文后面章节的研究奠定了基础。
2.提出了一种改进的极坐标随机Hough变换TBD算法，给出了选择最大采样次数的准则，利用帧与帧之间目标的运动信息抑制了大量的无效采样，采用最小距离投票准则克服了投票时的峰值展宽问题，所提算法的检测跟踪性能均优于传统的极坐标随机Hough变换TBD算法。
3.提出了一种距离扩展目标粒子滤波TBD算法。建立了距离扩展目标运动模型和多散射点的量测模型，提出了一种距离扩展目标粒子滤波TBD算法，实现了对距离扩展目标有无、运动状态和长度的同时估计，与最新的B-PF-TBD算法相比，检测和跟踪性能更高。
4.提出了自适应马尔可夫链蒙特卡洛（MCMC）采样的粒子滤波TBD多目标算法，通过自适应采样策略，对相互临近的目标联合采样，对彼此远离的目标逐一的独立采样，提高了算法的运算效率，与马尔可夫链蒙特卡洛粒子滤波TBD多目标算法相比，收敛速度更快；与基于重要性重采样的粒子滤波TBD多目标算法相比，跟踪精度更高。
5.提出了多帧相参积累TBD算法。通过对运动目标回波的分析，建立了多帧相参积累TBD算法的信号模型，基于该信号模型，推导了GLRT检测器，提出了一种高效的多帧相参积累TBD算法来估计目标的未知参数（目标所在的方位单元、距离单元、多普勒频率和调频斜率），实现了对多帧时间内目标回波的相参积累。推导了基于多帧相参积累TBD算法的GLRT检测器的检测概率和虚警概率的解析表达式，从理论上分析了算法的检测性能。最后采用仿真实验验证了信号模型的正确性和多帧相参积累TBD算法的有效性。
With the development and wide utilization of stealthy technology, the radar crosssection (RCS) of typical military targets, such as aircrafts, missels and combat ships,has been greatly decreased. The reflected signal from these targets is very weak causingsevere challenges to radar detection and tracking. The traditional Detect-Before-Track(DBT) methods cannot guarantee reliable detection and tracking performance whenencounted with these weak targets. Track-Before-Detect (TBD) methods are one of theeffective methods of detection and tracking weak targets, which jointly process severalconsecutive scans of unthresholded data to integrate the targets energy, jointly declearthe presence of the targets, and, enentually, its track. As a developing new technique,it’s urgent to investigate TBD theories, modifiy TBD methodologies and expend TBDapplication for weak targets in radar system which can improve detection and trackingperformances.
In this dissertation, TBD algorithm for weak targets in radar system is investigated.The main results are as follows:
1. The differences and the advantages and disadvantages of DBT methods andTBD methods are analysised and comparisoned. And TBD methods are classified ascoherent accumulation and non-coherent accumulation among the frames by the way ofenergy accumulation. The signal processing process and algorithms of the two ways arepresented, respectively. This chapter makes the theoretical foundation of the subsequentchapters of this thesis.
2. A modified polar random Hough transform based TBD algorithm (MP-RHT-TBD) is proposed. The criterion of maximum sampling number is presented. Thetargets’ motion information among frames is utilized to restrain the amount of invalidsampling, and the rule of voting by minimum distance overcomes the problem of peakbroadening. The MP-RHT-TBD algorithm has better detection and trackingperformaces than the P-RHT-TBD algorithm.
3. A particle filter based TBD algorithm for range extent targets is proposed. Themotion model and measurement model of multi-scatterers for range extent targets are built. A particle filter based TBD algorithm for range extent targets is proposed toestimate the presence/absence, the motion states and length of the range extent targets,simultaneously. By comparison with the existing TBD algorithm for extent targets, theproposed algorithm has better performance of the detection and tracking.
4. A novel PF-TBD based on adaptive Markov Chain Monte Carlo (MCMC) formulti-targets is proposed. By the adaptive sampling strategy, adjacent targets are jointsampled and far-away targets are independent sampled. This adaptive samplingimproves efficiency of algorithm and has better rate of convergence than MCMC-PF-TBD algorithm, and has better tracking precision than the SIR-PF-TBD algorithm.
5. A multi-frame coherent TBD technology is proposed. By the analysis of theechoes of the moving targets, a signal model for coherent accumulation among frames isbuilt. Based on the model, the GLRT detector is derived, and an efficient coherentaccumulation algorithm is proposed to estimate the unknown parameters of the target(targets’ azimuth, distance, Doppler and modulation slope). The analytical expressionsof false alarm and detection probabilitiy of GLRT detector based on the proposedalgorithm are derived, and the performance of detection of the algorithm is analyzedtheoretically. Finally, the validity of the signal model and the efficiency of the proposedalgorithm are verified by simulation experiments.
引文
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