適用於行動通訊系統之定位粒子濾波器設計與實作

Design and Implementation of Positioning Particle Filter for Cellular Communication Systems

莊慕軒(Mu-Hsuan Chuang)

指導教授 ： 黃元豪

國立清華大學/電機資訊學院/電機工程學系/碩士(2011年)

https://doi.org/10.6843/NTHU.2011.00565

摘要

中文摘要

本篇論文提出適用於行用通訊系統下多輸入多輸出特徵定位之界限型IMH粒子濾波器。我們提出的技術從兩個觀點來改善在室內與室外的定位精準度。以系統的觀點，於空間通道模型(TR25.996)下使用多輸入多輸出系統特徵增進定位精準度。以訊號處理的觀點，粒子濾波器可以成功地對抗非線性問題。應用於2x2 多輸入多輸出系統。就我們所知，唯一假設通道資訊非完美已知僅有我們所提出的多輸入多輸出特徵定位之粒子濾波器。模擬結果顯示多輸入多輸出特徵定位之粒子濾波器有很好的定位精準度，於Spacing為4公尺情形下平均時間的均方根誤差約為5公尺。
在硬體架構方面，我們所提出的界限型 IMH粒子濾波器可以使用管線化的硬體設計並且維持良好的精準度。在我們的設計裡捨棄在傳統IMH理論裡針對兩兩粒子weight大小去做比較的resampling方式。首先，我們將粒子上distance的資訊和resampling threshold做比較去決定是否要將粒子的資訊存起來或是被前一顆粒子的資訊所取代。第二，由於weight和distance之間的關係為一對一，我們可以使用distance去做為resampling時比較的依據，如此可以降低硬體的複雜度。管線化的硬體設計不只可以增加硬體的使用效率還可以增加資料的輸出量，將原本粒子濾波器硬體使用效率從35-40%提升到超過95%。此論文所設計的晶片採用ARM_3.2 TSMC 0.18um的製程及cell library去做設計，核心電路面積為1.48mm2，晶片面積為3.64mm2，正常運作頻率為106MHz。
總結此研究，在通道資訊並非完美已知的情形下多輸入多輸出系統特徵定位粒子濾波器增進了精準度，同時我們提出的架構也解決了運作速度與精準度之間tradeoff的問題，可以同時兼顧兩者達到高速以及高精準度的應用。
在未來的研究裡，將會真對多PE架構之粒子濾波器硬體做進一步的模擬和設計，以求得到更快的運算速度以符合未來更加高速的定位需求。

關鍵字

粒子濾波器 ； 實作 ； 硬體設計 ； ASIC

並列摘要

This thesis proposes a particle filter (PF) with threshold Independent Metropolis Hasting(IMH) resampling for the multiple input multiple output(MIMO) fingerprinting
positioning in the cellular system. The proposed technique improves the positioning accuracy in both indoor and outdoor conditions from two perspectives. For the system
perspective, the MIMO system with fingerprinting improves the transmitting diversity and positioning accuracy in the spatial channel model (TR25.996). For the digital signal processing perspective, the proposed particle filter can successfully address the non-linearity issue and combat the non-ideal effect in real channel condition.

The simulation results show that the proposed method has good positioning accuracy, about 5m RMSE when Spacing is equal to 4m. To solve the bottleneck of hardware design in the original particle filter, the thesis proposes threshold IMH resampling algorithm to replace traditional systematic resampling, which has low hardware utilization rate and long processing latency. Further, this thesis proposes selective sampling strategy to reduce the number of particle converging iterations and improve positioning
accuracy.

In the hardware architecture, this thesis designs flexible particle number and sampling threshold according different channel conditions. When the channel condition is bad, we use more particles to estimate the position. On the contrary, we can use fewer particles to reduce the latency. Moreover, using proposed threshold IMH resampling in the hardware, the hardware utilization rate can increase to more than 95% according different particles. Compared to the traditional systematic resampling which needs 3M + L cycles for an iteration, the total processing latency of my design is reduced to M + L cycles, where M is particle number and L is pipeline number.

This study uses ARM 3.2 TSMC-0.18um cell library to implement the particle filter hardware. The operating frequency of the chip is 106MHz when supply voltage is 1.8V.
The core area is 1.48mm2, and the chip area is 3.64mm2.

This thesis anticipates the the implemented particle filter chip is utilized in the base-station to localize mobile users. Hence, the high operating frequency is the major target we want to achieve to make Time-Division Multiple Access(TDMA) scheme practicable in the positioning system.
In the future work, we propose to research implementing our proposed threshold IMH resampling design into PE-CU architecture for further reducing the processing latency
of particle filter.

並列關鍵字

Particle Filter ； Implementation ； hardware design ； ASIC

參考文獻

[1] Spatial channel model for Multiple Input Multiple Output(MIMO) simulations(Rel.7), 3GPP Std. TR 25.996, Rev. 7.0.0, Jun. 2007.

[3] T. Wigren, “Adaptive Enhanced Cell-ID Fingerprinting Localization by Clustering of Precise Position

Measurements ,” IEEE Trans. Veh. Technol., vol. 56, no. 5, pp.3199–3209, Sep. 2007.

[5] A. Sankaranarayanan, R. Chellappa, and A. Srivastava, “Algorithmic and architectural design methodology for particle filters in hardware,” in Proc. Int. Conf.

[6] S. Bizjajeva, T. Ryden, and O. Edfors, “Mobile Positioning in MIMO System Using Particle Filtering,” in Proc. IEEE 66th Veh. Technol. Conference, Sep. 2007, pp.