基于多传感器零速修正的行人导航系统研究
|
摘要
针对行人导航定位系统中惯性导航解算误差累积问题,提出基于多传感器零速修正的行人三维导航定位方法。根据行人足部运动特征,采用支持向量机决策方法对行人运动和静止阶段进行检测分类。在静止阶段,根据多传感器测量数据对导航解算速度、角速度、方向和高度进行误差修正,采用卡尔曼滤波递推方法进行数据融合和滤波估计,实现对方向、位置和速度的跟踪。行人行走实验表明,设计的行人导航定位系统能够有效地跟踪行人行走轨迹,水平方向各楼层平均误差为1. 82%,高度方向平均误差为2. 53%。
Aiming at the accumulation problem of inertial navigation solver error in pedestrian navigation and positioning system,a pedestrian three-dimensional navigation and positioning method based on multi-sensor zero speed correction is proposed. According to the movement characteristics of pedestrian foot,the support vector machine decision-making method is used to detect and classify pedestrian movement and stationary stage. In the stationary stage,according to the multi-sensor data,the navigation solution speed,angular velocity,direction and height can be corrected,and the Kalman filter recursive method is used for data fusion and filter estimation to track the direction,position and speed. Pedestrian walking experiments show that the pedestrian navigation system can effectively track the walking trajectory of pedestrians. The average error of each floor in the horizontal direction is 1. 82%,and the average error in the height direction is 2. 53%.
Aiming at the accumulation problem of inertial navigation solver error in pedestrian navigation and positioning system,a pedestrian three-dimensional navigation and positioning method based on multi-sensor zero speed correction is proposed. According to the movement characteristics of pedestrian foot,the support vector machine decision-making method is used to detect and classify pedestrian movement and stationary stage. In the stationary stage,according to the multi-sensor data,the navigation solution speed,angular velocity,direction and height can be corrected,and the Kalman filter recursive method is used for data fusion and filter estimation to track the direction,position and speed. Pedestrian walking experiments show that the pedestrian navigation system can effectively track the walking trajectory of pedestrians. The average error of each floor in the horizontal direction is 1. 82%,and the average error in the height direction is 2. 53%.
引文
[1]PASSARO V,CUCCOVILLO A,VAIANI L,et al.Gyroscope technology and applications:A review in the industrial perspective[J].Sensors,2017,17(10):2284.
[2]LI J,WANG Q,LIU X,et al.A pedestrian dead reckoning system integrating low-cost MEMS inertial sensors and GPS receiver[J].Journal of Engineering Science and Technology Review,2014,7(2):197-203.
[3]CHANG L,LI J,CHEN S.Initial alignment by attitude estimation for strapdown inertial navigation systems[J].IEEE Transactions on Instrumentation and Measurement,2015,64(3):784-794.
[4]LYSHEVSKI S E.Signal processing in cyber-physical MEMS sensors:Inertial measurement and navigation systems[J].IEEE Transactions on Industrial Electronics,2017,64(12):9618-9625.
[5]CHENG J T,YANG L,LI Y,et al.Seamless outdoor/indoor navigation with WIFI/GPS aided low cost inertial navigation system[J].Physical Communication,2014(13):31-43.
[6]MUNOZ D E,CAAMANO M,SANCHEZ F.Landmarkbased drift compensation algorithm for inertial pedestrian navigation[J].Sensors,2017,17(7):1555.
[7]陈兴秀,张金艺,晏理,等.三维复杂运动模式航迹推算惯性导航室内定位[J].应用科学学报,2014,32(4):349-356.CHEN X X,ZHANG J Y,YAN L,et al.Inertial indoor navigation with 3D complex motion mode of pedestrian dead reckoning[J].Journal of Applied Sciences,2014,32(4):349-356.
[8]FOURATI H.Heterogeneous data fusion algorithm for pedestrian navigation via foot-mounted inertial measurement unit and complementary filter[J].IEEETransactions on Instrumentation and Measurement,2015,64(1):221-229.
[9]PELTOLA P,HILL C,MOORE T.Particle filter for context sensitive indoor pedestrian navigation[C].IEEEInternational Conference on Localization and GNSS(ICL-GNSS),2016:1-6.
[10]樊启高,孙艳,孙璧文,等.基于GLRT零速检测算法的行人室内定位系统[J].传感技术学报,2017,30(11):1706-1711.FAN Q G,SUN Y,SUN B W,et al.Pedestrian indoor positioning system based on GLRT zero speed detection[J].Chinese Journal of Sensors and Actuators,2017,30(11):1706-1711.
[11]KIM H,LEE S,LEE D,et al.Real-time human pose estimation and gesture recognition from depth images using superpixels and SVM classifier[J].Sensors,2015,15(6):12410-12427.
[12]李欢,王士同.支持向量机的多观测样本二分类算法[J].智能系统学报,2014,9(4):392-400.LI H,WANG SH T.Binary-class classification algorithm with multiple-access acquired objects based on the SVM[J].CAAI Transactions on Intelligent Systems,2014,9(4):392-400.
[13]ZHENG Z,HAN S,ZHENG K.An eight-position selfcalibration method for a dual-axis rotational inertial navigation system[J].Sensors and Actuators A:Physical,2015(232):39-48.
[14]孙伟,李松,李瑞豹,等.基于零速修正的采煤机测姿技术研究[J].电子测量与仪器学报,2015,29(12):1829-1835.SUN W,LI S,LI R B,et al.Research on attitude determination technology of mining machine based on ZUPT[J].Journal of Electronic Measurement and Instrumentation,2015,29(12):1829-1835.
[15]王晓雷,闫双建,张吉涛,等.气压高度测量系统的设计与实现[J].自动化仪表,2017,38(8):59-63.WANG X L,YAN SH J,ZHANG J T,et al.Design and realization of barometric pressure height measurement system[J].Process Automation Instrumentation,2017,38(8):59-63.
[16]NORRDINE A,KASMI Z,BLANKENBACH J.Step detection for ZUPT-aided inertial pedestrian navigation system using foot-mounted permanent magnet[J].IEEESensors Journal,2016,16(17):6766-6773.
[17]LI H,PAN Q,WANG X,et al.Kalman filter design for initial precision alignment of a strapdown inertial navigation system on a rocking base[J].The Journal of Navigation,2015,68(1):184-195.
[2]LI J,WANG Q,LIU X,et al.A pedestrian dead reckoning system integrating low-cost MEMS inertial sensors and GPS receiver[J].Journal of Engineering Science and Technology Review,2014,7(2):197-203.
[3]CHANG L,LI J,CHEN S.Initial alignment by attitude estimation for strapdown inertial navigation systems[J].IEEE Transactions on Instrumentation and Measurement,2015,64(3):784-794.
[4]LYSHEVSKI S E.Signal processing in cyber-physical MEMS sensors:Inertial measurement and navigation systems[J].IEEE Transactions on Industrial Electronics,2017,64(12):9618-9625.
[5]CHENG J T,YANG L,LI Y,et al.Seamless outdoor/indoor navigation with WIFI/GPS aided low cost inertial navigation system[J].Physical Communication,2014(13):31-43.
[6]MUNOZ D E,CAAMANO M,SANCHEZ F.Landmarkbased drift compensation algorithm for inertial pedestrian navigation[J].Sensors,2017,17(7):1555.
[7]陈兴秀,张金艺,晏理,等.三维复杂运动模式航迹推算惯性导航室内定位[J].应用科学学报,2014,32(4):349-356.CHEN X X,ZHANG J Y,YAN L,et al.Inertial indoor navigation with 3D complex motion mode of pedestrian dead reckoning[J].Journal of Applied Sciences,2014,32(4):349-356.
[8]FOURATI H.Heterogeneous data fusion algorithm for pedestrian navigation via foot-mounted inertial measurement unit and complementary filter[J].IEEETransactions on Instrumentation and Measurement,2015,64(1):221-229.
[9]PELTOLA P,HILL C,MOORE T.Particle filter for context sensitive indoor pedestrian navigation[C].IEEEInternational Conference on Localization and GNSS(ICL-GNSS),2016:1-6.
[10]樊启高,孙艳,孙璧文,等.基于GLRT零速检测算法的行人室内定位系统[J].传感技术学报,2017,30(11):1706-1711.FAN Q G,SUN Y,SUN B W,et al.Pedestrian indoor positioning system based on GLRT zero speed detection[J].Chinese Journal of Sensors and Actuators,2017,30(11):1706-1711.
[11]KIM H,LEE S,LEE D,et al.Real-time human pose estimation and gesture recognition from depth images using superpixels and SVM classifier[J].Sensors,2015,15(6):12410-12427.
[12]李欢,王士同.支持向量机的多观测样本二分类算法[J].智能系统学报,2014,9(4):392-400.LI H,WANG SH T.Binary-class classification algorithm with multiple-access acquired objects based on the SVM[J].CAAI Transactions on Intelligent Systems,2014,9(4):392-400.
[13]ZHENG Z,HAN S,ZHENG K.An eight-position selfcalibration method for a dual-axis rotational inertial navigation system[J].Sensors and Actuators A:Physical,2015(232):39-48.
[14]孙伟,李松,李瑞豹,等.基于零速修正的采煤机测姿技术研究[J].电子测量与仪器学报,2015,29(12):1829-1835.SUN W,LI S,LI R B,et al.Research on attitude determination technology of mining machine based on ZUPT[J].Journal of Electronic Measurement and Instrumentation,2015,29(12):1829-1835.
[15]王晓雷,闫双建,张吉涛,等.气压高度测量系统的设计与实现[J].自动化仪表,2017,38(8):59-63.WANG X L,YAN SH J,ZHANG J T,et al.Design and realization of barometric pressure height measurement system[J].Process Automation Instrumentation,2017,38(8):59-63.
[16]NORRDINE A,KASMI Z,BLANKENBACH J.Step detection for ZUPT-aided inertial pedestrian navigation system using foot-mounted permanent magnet[J].IEEESensors Journal,2016,16(17):6766-6773.
[17]LI H,PAN Q,WANG X,et al.Kalman filter design for initial precision alignment of a strapdown inertial navigation system on a rocking base[J].The Journal of Navigation,2015,68(1):184-195.