基于信号到达时间差的超宽带室内定位算法
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摘要
超宽带(UWB)信号具有极大的带宽和极高的时间分辨率,非常适合室内精确定位,基于信号到达时间差(TDOA)的定位算法是UWB定位的首选方法。针对非视距(NLOS)环境下定位精度低的问题,提出了一种结合Chan算法对非视距误差进行鉴别和消减的TDOA定位算法。首先,利用Chan算法估计出移动目标的初始位置并计算出TDOA测量误差,然后对比误差门限进行NLOS鉴别和消减,最后再次使用Chan算法计算出移动目标的精确位置。仿真实验表明,增加定位基站个数、减小信号测量噪声和非视距误差,可以有效提高定位精度;与Chan算法相比,改进算法:在只有一个非视距基站的情况下,均方根误差平均减小了39. 55%;在有三个非视距基站的情况下,均方根误差平均减小了56. 06%。该算法具有更高的定位精度。
Ultra-WideBand( UWB) signals with great bandwidth and high temporal resolution make them ideal for indoor precise positioning. The location algorithm based on Time Difference Of Arrival( TDOA) is the preferred method of UWB positioning. Concerning the problem of low localization accuracy in Non-Line Of Sight( NLOS) environment, an improved TDOA algorithm combined with Chan algorithm was proposed to identify and migrate NLOS error. Firstly, Chan algorithm was used to estimate the initial position of the moving target and calculate the TDOA measurement error. Secondly, the contrast error threshold was identified and subtracted by NLOS. Finally, Chan algorithm was used again to calculate the exact position of the moving target. The simulation results show that the number of positioning base stations is increased, the signal measurement noise and NLOS error is reduced, which can effectively improve the positioning accuracy. Compared with Chan algorithm, the proposed algorithm reduces average root mean square error by 39. 55% with only one NLOS base station and 56. 06% with three NLOS base stations. The proposed algorithm has higher positioning accuracy.
Ultra-WideBand( UWB) signals with great bandwidth and high temporal resolution make them ideal for indoor precise positioning. The location algorithm based on Time Difference Of Arrival( TDOA) is the preferred method of UWB positioning. Concerning the problem of low localization accuracy in Non-Line Of Sight( NLOS) environment, an improved TDOA algorithm combined with Chan algorithm was proposed to identify and migrate NLOS error. Firstly, Chan algorithm was used to estimate the initial position of the moving target and calculate the TDOA measurement error. Secondly, the contrast error threshold was identified and subtracted by NLOS. Finally, Chan algorithm was used again to calculate the exact position of the moving target. The simulation results show that the number of positioning base stations is increased, the signal measurement noise and NLOS error is reduced, which can effectively improve the positioning accuracy. Compared with Chan algorithm, the proposed algorithm reduces average root mean square error by 39. 55% with only one NLOS base station and 56. 06% with three NLOS base stations. The proposed algorithm has higher positioning accuracy.
引文
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[2]万群,郭贤生,陈章鑫.室内定位理论、方法和应用[M].北京:电子工业出版社,2012:54-70.
[3]FANG B T. Simple solutions for hyperbolic and related position fixes[J]. IEEE Transactions on Aerospace&Electronic Systems, 1990,26(5):748-753.
[4]谢胜东,胡爱群,黄毅,等.基于到达时间差的两步最小二乘定位算法[J].东南大学学报(自然科学版),2013,43(6):1157-1161.
[5]CHAN Y T, HO K C. A simple and efficient estimator for hyperbolic location[J]. IEEE Transactions on Signal Processing, 1994, 42(8):1905-1915.
[6]FOY W H. Position-location solutions by Taylor-series estimation[J]. IEEE Transactions on Aerospace&Electronic Systems, 2007,AES-12(2):187-194.
[7]ALAVI B, PAHLAVAN K. Modeling of the TOA-based distance measurement error using UWB indoor radio measurements[J].IEEE Communications Letters, 2006, 10(4):275-277.
[8]王洪雁,陈黎霞,裴炳南. NLOS环境下TDOA/AOA混合定位算法研究[J].计算机应用,2007,27(5):1099-1102.
[9]CASSIOLI D, WIN M Z, VATALARO F, et al. Low complexity Rake receivers in ultra-wideband channels[J]. IEEE Transactions on Wireless Communications, 2007, 6(4):1265-1275.
[10]SCHOLTZ R A. Multiple access with time-hopping impulse modulation[C]//MILCOM'93:Proceedings of the 1993 IEEE Military Communications Conference. Piscataway, NJ:IEEE, 1993, 2:447-450.
[11]魏培,姜平,贺晶晶,等.基于内三角形质心算法的超宽带室内定位[J].计算机应用,2017,37(1):289-293.
[12]SUBRAMANIAN A. UWB linear quadratic frequency domain frequency invariant beamforming and angle of arrival estimation[C]//Proceedings of the 2007 IEEE Vehicular Technology ConferenceVtc2007-Spring. Piscataway, NJ:IEEE, 2007:614-618.
[13]IWAKIRI N, KOBAYASHI T. Joint TOA and AOA estimation of uwb signal using time domain smoothing[C]//Proceedings of the2007 2nd International Symposium on Wireless Pervasive Computing. Piscataway, NJ:IEEE, 2007:Article No. 23.
[14]丁锐,钱志鸿,王雪.基于TOA和DOA联合估计的UWB定位方法[J].电子与信息学报,2010,32(2):313-317.
[15]GUVENC I, CHONG C C, WATANABE F. NLOS identification and mitigation for UWB localization systems[C]//Proceedings of the 2007 Wireless Communications and Networking Conference.Piscataway, NJ:IEEE, 2007:1571-1576.
[16]WANN C D, HSUEH C S. NLOS mitigation with biased Kalman filters for range estimation in UWB systems[C]//TENCON 2007:Proceedings of the 2007 IEEE Region 10 Conference. Piscataway,NJ IEEE, 2008:1-4
[17]WYLIE M P, HOLTZMAN J. The non-line of sight problem in mobile location estimation[C]//Proceedings of the 1996 IEEE International Conference on Universal Personal Communications. Piscataway, NJ:IEEE, 1996, 2:827-831.
[18]BORRS J, HATRACK P, MANDAYAM N B. Decision theoretic framework for NLOS identification[C]//Proceedings of the 1998IEEE Vehicular Technology Conference. Piscataway, NJ:IEEE,1998, 2:1583-1587.
[19]罗磊,田增山,孙冬梅,等.基站几何布局对定位误差的影响[J].通信技术,2008,41(2):126-128.