Indoor moving target positioning method based on trajectory smoothing

Abstract

The invention puts forward an indoor moving target positioning method based on trajectory smoothing, comprising the following steps: (1) a mobile UWB (Ultra Wideband) node acquires the distance between the node and each anchor node through polling; (2) the distance measured by each anchor node at a moment is corrected by an unscented Kalman filter; (3) the position coordinate of a moving target is acquired through a trilateration positioning approach based on the filtered UWB measured value at the moment; (4) the positioning result is corrected by the unscented Kalman filter; and (5) the filtered positioning result is smoothed by an adaptive smoothing algorithm so as to reach the position estimated value of the moving target at the current moment. According to the invention, the measured values and estimated values at the current moment and at a previous moment are fully utilized, an unscented Kalman filtering mode is adopted, so the influence of environment, device and other factors on the measurement result is reduced, and the positioning accuracy of the trilateration approach is improved; and the positioning result is filtered secondarily and smoothed adaptively, and the positioning accuracy is further improved.

Description

technical field [0001] The invention relates to a target positioning method, in particular to a track smoothing-based indoor moving target positioning method. Background technique [0002] How to achieve high-precision positioning of indoor moving targets is one of the key points in the research of indoor positioning systems. Among the existing positioning technologies, UWB technology can achieve centimeter-level ranging accuracy. The UWB module calculates the distance between modules by measuring the time of flight (TOF, TimeofFlight) of the signal in the air. However, in practical applications, it is found that the complex indoor environment makes the transmission of electromagnetic waves quite different under line-of-sight conditions and non-line-of-sight conditions. In addition, when affected by external factors, UWB devices will cause large deviations in ranging results , directly affects the result of trilateration. The existing method is to assume that the noise is...

AI Technical Summary

Problems solved by technology

However, in practical applications, it is found that the complex indoor environment makes the transmission of electromagnetic waves quite different under line-of-sight conditions and non-line-of-sight conditions. In addition, when affected by external factors, UWB devices will cause large deviations in ranging results , which directly affects the results of the trilateration

The existing method is to assume that the noise is Gaussian noise with zero mean value, and perform Kalman filtering on the measurement results, but the actual measurement noise does not obey the standard normal distribution, and unscented Kalman filtering is required

In addition, the trilateration method obtains the least squares solution that satisfies the conditions. When there is a slight deviation in some anchor nodes, the positioning result will have a large deviation.

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