Losing lock detection method based on extended Kalman filter tracking loop in GPS receiver

Abstract

The invention provides a losing lock detection method based on an extended Kalman filter tracking loop in a GPS receiver. According to a characteristic that a loop gain in an extended Kalman filter can dynamically change with change of a measured value, through a gain variable in the loop, whether the loop is in losing lock or not is detected. In the extended Kalman filter, through a state estimation mean square deviation matrix P, a process noise covariance matrix Q, a measurement noise covariance matrix R and a TS filtering equation, an intermediate variable b and a Kalman filtering gain K are calculated, and through subtracting an observation variable matrix estimated value and the intermediate variable b from an observation variable matrix, an residual error is obtained. By multiplying the residual error by the Kalman filtering gain K, a carrier loop gain coefficient matrix G is obtained. An accumulated value of a parameter G (1, 1) in the first row and in the first column of the matrix G is taken as a loop losing locking detection criterion. When the accumulated value of G (1, 1) obtained by accumulating for 100 times of the parameter G (1, 1) exceeds a threshold, the loop losing lock is determined.

Description

technical field [0001] The invention relates to an out-of-lock detection method for a GPS receiver based on an extended Kalman filter tracking loop, and belongs to the technical field of GPS communication. Background technique [0002] Kalman filters are described by a series of recursive mathematical formulas. It provides an efficient and computable way to estimate the state of the process and minimize the estimated mean squared error. The algorithm used by the Kalman filter is different from the traditional carrier tracking loop. It replaces the structure of the phase detector plus filter in the traditional carrier loop. Its carrier tracking loop gain can change with the change of the measured value. Dynamic changes, so as to achieve high sensitivity and high dynamic tracking, thereby greatly improving the tracking performance of the receiver. Since the gain of the carrier tracking loop in the extended Kalman filter can change dynamically, it is a simple and effective wa...

AI Technical Summary

Problems solved by technology

At present, there have been a few studies on the extended Kalman filter as the tracking loop of the GPS receiver, but there is no use of the dynamic parameters in it as the detection of loop loss

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