Abstract
The angular position measurement of an array antenna based on a wireless signal has high accuracy in an indoor no-occlusion environment. However, due to the high complexity of indoor environments, signal occlusion, multipath, and other interfering factors are inevitable when users move randomly, which can greatly reduce the positioning accuracy. In addition, different directions of the positioning source signal can also affect the positioning result. The switching wheels of the dual-polarization antenna array are collected in channel 1, the fast Fourier transform (FFT) is applied to the data of channel 2 to estimate the frequency offset, and the phase of the data is compensated. Using the FFT frequency offset estimation, the high-precision positioning of a single base station is realized using the dual-channel switch and dual-polarization antenna array in turn. Aiming at analyzing the affecting factors of the positioning system accuracy, the strong tracking kalman filter algorithm is studied. At the same time, the singular value decomposition of the covariance matrix is performed to improve the robustness of the strong tracking kalman filter, and the adaptive factor is introduced to improve the filtering accuracy. The proposed positioning algorithm can achieve the positioning accuracy within 1 m in the coverage area in a line-of-sight (LOS) environment, while the dynamic positioning accuracy within 1 m cannot be guaranteed in the coverage area in a non-line-of-sight (NLOS) environment. On this basis, the analysis of the static, rotational, and dynamic positioning accuracies of the source in the LOS and NLOS environments shows that the proposed singular value decomposition strong tracking kalman filter (SVD-STKF) algorithm can improve the overall positioning accuracy of the system by 0.03 m, and the maximum error in the LOS environment can be reduced by 0.08 m. The proposed SVD-STKF algorithm can correct the Hausdorff distance of dynamic positioning by up to 0.513 m in the NLOS environment where the system’s positioning accuracy decreases sharply due to the signal shielding. Also, it can make the positioning results smoother and achieve a good correction effect for the points far away from the true trajectory.
Highlights
The switching wheels of the dual-polarization antenna array are collected in turn in channel 1, the fast Fourier transform (FFT) is applied to the data of channel 2 to estimate the frequency offset, and the phase of the data is compensated, without eliminating the frequency estimation error through phase comparison
According to Equation (7), the multipath and other factors in the echo signal of the receiver cannot be eliminated, and the characteristics of the reflected signals vary with the material and size of obstacles
If the signal is not affected by environmental factors, such as refraction, reflection, and multipath effect, it can be considered that rk obeys the Gaussian distribution with the zero mean
Summary
The switching wheels of the dual-polarization antenna array are collected in turn in channel 1, the fast Fourier transform (FFT) is applied to the data of channel 2 to estimate the frequency offset, and the phase of the data is compensated, without eliminating the frequency estimation error through phase comparison It can achieve high precision positioning within the coverage area of a single base station. In a complex indoor environment, it is obviously difficult to guarantee Aiming to solve this problem, many adaptive filtering algorithms based on the estimation algorithm of statistical characteristics of time-varying noise have been proposed. Q of the system noise and the covariance matrix R of the measurement noise are uncertain, the adaptive filtering uses the information on the observed data to estimate and correct the statistical characteristics of the noise continuously so as to reduce the state estimation error [23,24].
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