WiFi fingerprinting is the method of recording WiFi signal strength from access points （AP） along with the positions at which they were recorded, and later matching those to new mea- surements for indoor positioning...WiFi fingerprinting is the method of recording WiFi signal strength from access points （AP） along with the positions at which they were recorded, and later matching those to new mea- surements for indoor positioning. Inertial positioning utilizes the accelerometer and gyroscopes for pedestrian positioning. However, both methods have their limitations, such as the WiFi fluctuations and the accumulative error of inertial sensors. Usually, the filtering method is used for integrating the two approaches to achieve better location accuracy. In the real environments, especially in the indoor field, the APs could be sparse and short range. To overcome the limitations, a novel particle filter approach based on Rao Blackwellized particle filter （RBPF） is presented in this paper. The indoor environment is divided into several local maps, which are assumed to be independent of each other. The local areas are estimated by the local particle filter, whereas the global areas are com- bined by the global particle filter. The algorithm has been investigated by real field trials using a WiFi tablet on hand with an inertial sensor on foot. It could be concluded that the proposed method reduces the complexity of the positioning algorithm obviously, as well as offers a significant improvement in position accuracy compared to other conventional algorithms, allowing indoor positioning error below 1.2 m.展开更多
将声表面波传感器与信号无线保真(WIFI)技术相结合,提出了一种基于WIFI的无线声表面波传感器信号采集系统。该系统由声表面波传感器、信号调理电路、处理器、WIFI模块和无线接收终端组成。声表面波传感器混频后的信号经过信号调理电路后...将声表面波传感器与信号无线保真(WIFI)技术相结合,提出了一种基于WIFI的无线声表面波传感器信号采集系统。该系统由声表面波传感器、信号调理电路、处理器、WIFI模块和无线接收终端组成。声表面波传感器混频后的信号经过信号调理电路后,转换为处理器可计频的低频方波信号,并通过WIFI模块将采集到的信号无线发送到接收终端。通过一个输出信号范围在100 k Hz^350 k Hz声表面波传感器信号采集系统的实现,对该系统的结构、性能进行了验证和测试。实验结果表明,该系统可以实现测试范围内信号的采集、发送和无线接收,系统输入信号与无线接收终端接收信号之间的平均绝对误差为0.843 k Hz,最大相对误差为0.51%,无障碍环境有效采集范围约为100 m,有障碍环境有效采集范围约为50 m。展开更多
文摘WiFi fingerprinting is the method of recording WiFi signal strength from access points （AP） along with the positions at which they were recorded, and later matching those to new mea- surements for indoor positioning. Inertial positioning utilizes the accelerometer and gyroscopes for pedestrian positioning. However, both methods have their limitations, such as the WiFi fluctuations and the accumulative error of inertial sensors. Usually, the filtering method is used for integrating the two approaches to achieve better location accuracy. In the real environments, especially in the indoor field, the APs could be sparse and short range. To overcome the limitations, a novel particle filter approach based on Rao Blackwellized particle filter （RBPF） is presented in this paper. The indoor environment is divided into several local maps, which are assumed to be independent of each other. The local areas are estimated by the local particle filter, whereas the global areas are com- bined by the global particle filter. The algorithm has been investigated by real field trials using a WiFi tablet on hand with an inertial sensor on foot. It could be concluded that the proposed method reduces the complexity of the positioning algorithm obviously, as well as offers a significant improvement in position accuracy compared to other conventional algorithms, allowing indoor positioning error below 1.2 m.
文摘将声表面波传感器与信号无线保真(WIFI)技术相结合,提出了一种基于WIFI的无线声表面波传感器信号采集系统。该系统由声表面波传感器、信号调理电路、处理器、WIFI模块和无线接收终端组成。声表面波传感器混频后的信号经过信号调理电路后,转换为处理器可计频的低频方波信号,并通过WIFI模块将采集到的信号无线发送到接收终端。通过一个输出信号范围在100 k Hz^350 k Hz声表面波传感器信号采集系统的实现,对该系统的结构、性能进行了验证和测试。实验结果表明,该系统可以实现测试范围内信号的采集、发送和无线接收,系统输入信号与无线接收终端接收信号之间的平均绝对误差为0.843 k Hz,最大相对误差为0.51%,无障碍环境有效采集范围约为100 m,有障碍环境有效采集范围约为50 m。
