本文關(guān)鍵詞： UWB 無線傳感器網(wǎng)絡(luò) 卡爾曼濾波 C# 混合編程　出處：《山東大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

【摘要】：近年來,隨著無線傳感器網(wǎng)絡(luò)的飛速發(fā)展,無線定位技術(shù)也越來越受到人們的關(guān)注。傳統(tǒng)的定位如紅外線、藍(lán)牙、超聲波、RFID等技術(shù),在定位精度、系統(tǒng)功耗等方面不能滿足人們的需求。而超寬帶(Ultra Wide Band, UWB)技術(shù)具有傳輸速率高、發(fā)射功率低、抗干擾和穿透能力強(qiáng)等特點(diǎn),特別是UWB定位具有非常高的定位精度,因此對(duì)UWB定位技術(shù)的研究具有重要的應(yīng)用價(jià)值。 本文通過對(duì)UWB定位平臺(tái)的需求分析和實(shí)際硬件情況,分別進(jìn)行了算法和上位機(jī)軟件的研究應(yīng)用,并對(duì)系統(tǒng)架構(gòu)進(jìn)行了設(shè)計(jì)。在定位算法方面,本文在UWB定位系統(tǒng)的平臺(tái)上,對(duì)Fang算法、Chan算法等經(jīng)典定位算法以及分別基于TOA和TDOA的擴(kuò)展卡爾曼濾波算法進(jìn)行了仿真研究,針對(duì)傳播過程中環(huán)境等因素造成的非視距誤差,運(yùn)用有偏卡爾曼濾波算法進(jìn)行了非視距誤差的抑制。 仿真發(fā)現(xiàn)傳統(tǒng)定位算法在可視距距差較小時(shí)能達(dá)到比較高的精度,但是隨著誤差的增大,算法性能有著顯著下降。其中,Fang算法不能利用冗余信息提高定位精度,Chan算法的性能在非視距環(huán)境中顯著下降,而卡爾曼濾波算法能有效地抑制測(cè)量誤差和非視距誤差的影響。本文重點(diǎn)研究了卡爾曼濾波的定位算法和非視距誤差的抑制算法,首先對(duì)初始到達(dá)時(shí)間測(cè)量值進(jìn)行有偏卡爾曼濾波抑制其非視距誤差,然后利用處理后的測(cè)量值進(jìn)行擴(kuò)展卡爾曼濾波定位。后續(xù)章節(jié)的仿真和應(yīng)用實(shí)例表明,該算法比傳統(tǒng)定位算有非常好的定位效果,在非視距誤差環(huán)境中也能達(dá)到較高的定位精度。 本文的主要目的在于將卡爾曼濾波算法應(yīng)用于PLUS定位平臺(tái)上,基于Visual Studio2012開發(fā)環(huán)境,使用C#和MATLAB混合編程的方式實(shí)現(xiàn),由于MATLAB提供了相當(dāng)豐富的矩陣運(yùn)算函數(shù),對(duì)卡爾曼濾波算法非常實(shí)用,卡爾曼濾波算法經(jīng)由MATLAB編譯為動(dòng)態(tài)鏈接庫(kù)文件,執(zhí)行效率高,易于維護(hù)。軟件采用C#編程來達(dá)到對(duì)移動(dòng)臺(tái)的實(shí)時(shí)定位,軟件運(yùn)行過程中實(shí)現(xiàn)了數(shù)據(jù)處理、計(jì)算機(jī)繪圖、數(shù)據(jù)保存、數(shù)據(jù)顯示以及多項(xiàng)任務(wù)的實(shí)時(shí)并行處理,提高了數(shù)據(jù)處理的效率。 實(shí)驗(yàn)結(jié)果表明,本文設(shè)計(jì)的定位系統(tǒng)能滿足定位的需要,軟件運(yùn)行穩(wěn)定且實(shí)時(shí)性好,所設(shè)計(jì)的算法提高了定位精度,降低了UWB系統(tǒng)的定位誤差。
[Abstract]:In recent years, with the rapid development of wireless sensor networks, wireless positioning technology has been paid more and more attention. Traditional positioning technology, such as infrared, Bluetooth, ultrasonic RFID and other technologies, in the positioning accuracy. The system power consumption and other aspects can not meet the needs of people, while ultra-wideband (UWB) technology has high transmission rate and low transmission power. The characteristics of anti-jamming and strong penetration, especially UWB positioning has a very high positioning accuracy, so the study of UWB positioning technology has an important application value. In this paper, the requirements of the UWB positioning platform and the actual hardware situation, respectively, algorithms and host computer software research and application, and the design of the system architecture. In the positioning algorithm. In this paper, on the platform of UWB positioning system, the classical localization algorithms such as Fang algorithm and extended Kalman filter algorithm based on TOA and TDOA are simulated. Aiming at the non-line-of-sight error caused by environmental factors in the process of propagation, the offset Kalman filter algorithm is used to suppress the non-line-of-sight error. Simulation results show that the traditional positioning algorithm can achieve a higher accuracy when the visual distance difference is small, but with the increase of the error, the performance of the algorithm has a significant decline. The Fang algorithm can not use redundant information to improve the positioning accuracy. The performance of the Fang algorithm is significantly reduced in the non-line-of-sight environment. The Kalman filter algorithm can effectively suppress the influence of measurement error and non-line-of-sight error. This paper focuses on the Kalman filter location algorithm and non-line-of-sight error suppression algorithm. First, the non-line-of-sight error is suppressed by biased Kalman filter, and then the extended Kalman filter is used to locate the measured value. The simulation and application examples of the following chapters show that the proposed method can be used to solve the problem of non-line-of-sight error. The algorithm has a better localization effect than the traditional positioning algorithm, and it can also achieve high positioning accuracy in the non-line-of-sight error environment. The main purpose of this paper is to apply the Kalman filter algorithm to the PLUS location platform, based on the Visual Studio2012 development environment. Using C # and MATLAB mixed programming, because MATLAB provides a lot of matrix operation functions, it is very practical to Kalman filter algorithm. The Kalman filter algorithm is compiled into dynamic link library file by MATLAB, which is efficient and easy to maintain. The software uses C # programming to locate the mobile station in real time. Data processing, computer drawing, data saving, data display and real-time parallel processing of many tasks are realized in the process of software operation, and the efficiency of data processing is improved. The experimental results show that the positioning system designed in this paper can meet the needs of location, and the software runs stably and real-time. The algorithm designed improves the positioning accuracy and reduces the positioning error of UWB system.
【學(xué)位授予單位】：山東大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TN925

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本文編號(hào)：1452824