Easy-hardware-implementation MMPF for Maneuvering Target Tracking: Algorithm and Architecture
Easy-hardware-implementation MMPF for Maneuvering Target Tracking: Algorithm and Architecture
复制标题
用于机动目标跟踪的易于硬件实现的 MMPF：算法和架构
DOI：
10.1007/s11265-010-0450-4
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发表时间：
2010-12
影响因子：
1.8
通讯作者：
Hong, Shaohua
中科院分区：
文献类型：
--
作者：
Shi, Zhiguo;Chen, Kangsheng;Hong, Shaohua
本文提出了一种易于硬件实现的多模型粒子滤波器（MMPF）用于机动目标跟踪。在该滤波器中，将通常用于非线性和/或非高斯应用的采样重要性恢复（SIR）滤波器扩展为包含由恒速（CV）模型和“当前”统计（CS）模型组成的多个模型，并将独立大都会黑斯廷斯（IMH）采样器用于每个模型中的恢复单元。与Bootstrap MMPF相比，该方法不需要知道不同机动运动的模型和模型转移概率，且每个模型的粒子数始终保持恒定.这允许规则的流水线硬件结构，并且可以容易地在硬件中实现。此外，使用IMH采样器的重采样单元避免了传统的系统重采样器引入的瓶颈，并减少了整个实现的延迟。仿真结果表明，该滤波器具有与自举MMPF近似相等的跟踪性能。给出了IMH采样器及其采样单元的硬件结构，并描述了由CV模型处理单元（PE）、CS模型处理单元（PE）和中央单元（CU）组成的并行结构。该架构在Xilinx Virtex-II Pro FPGA平台上进行了机动目标跟踪应用的评估，结果表明，所提出的MMPF在效率、延迟低和易于硬件实现方面优于现有方法。
In this paper, we present an easy-hardware-implementation multiple model particle filter (MMPF) for maneuvering target tracking. In the proposed filter, the sampling importance resampling (SIR) filter typically used for nonlinear and/or non-Gaussian application is extended to incorporating multiple models that are composed of a constant velocity (CV) model and a “current” statistical (CS) model, and the Independent Metropolis Hasting (IMH) sampler is utilized for the resampling unit in each model. Compared with the bootstrap MMPF, the proposed MMPF requires no knowledge of models and model transition probabilities for different maneuvering motions, and keeps a constant number of particles per model at all times. This allows a regular pipelined hardware structure and can be implemented in hardware easily. Furthermore, using the IMH sampler for the resampling unit avoids the bottleneck introduced by the traditional systematic resampler and reduces the latency of the whole implementation. Simulation results indicate that the proposed filter has approximately equal tracking performance with the bootstrap MMPF. Hardware architecture of the IMH sampler and its corresponding sample unit are presented, and a parallel architecture consisting of CV model processing element (PE), CS model PE and a central unit (CU) is described. The proposed architecture is evaluated on a Xilinx Virtex-II Pro FPGA platform for a maneuvering target tracking application and the results show many advantages of the proposed MMPF over existing approaches in terms of efficiency, lower latency, and easy hardware implementation.
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影响因子：
2.3
作者：
Chen, Ji-Ming;Shi, Zhi-Guo;Chen, Kang-Sheng;Hong, Shao-Hua
通讯作者：
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影响因子：
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DOI：
10.1049/ip-rsn:20030741
发表时间：
2003-10-01
期刊：
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影响因子：
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通讯作者：
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DOI：
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发表时间：
1995-10
期刊：
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影响因子：
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DOI：
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期刊：
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影响因子：
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