改进粒子滤波的弱目标跟踪与检测

基于粒子滤波的检测前跟踪技术（TBD\|PF）是低信噪比环境下目标检测与跟踪的有效方法。针对传统的TBD\|PF算法经重采样后容易导致粒子耗尽,从而跟丢目标的缺点。本文提出采用对权重较低的部分“存活”粒子用“新生”粒子将其替换,且对重采样后的粒子实施马尔科夫链蒙特卡洛（MCMC）移动步骤的粒子更新策略,在增加粒子多样性的同时保证了粒子的有效性。仿真实验分析了粒子数大小,预设门限的选取对检测性能的影响。实验结果表明,所提算法的检测与跟踪性能要优于传统的粒子滤波算法。
     

Multiple model particle flter track-before-detect for range ambiguous radar

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.     

Multiframe weak target track-before-detect based on pseudo-spectrum in mixed coordinates

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 a...