Error estimation method and system for multi-sensor system

Abstract

The invention discloses an error estimation method and system for a multi-sensor system. A specific embodiment of the method includes: collecting measurement data involved in system error estimation according to a preset estimation cycle; The discretization model of the position difference of the same target in the geographic coordinate system at the same time, the estimated value of the systematic error and the related quantity of the measured data obtains the estimated value of the systematic error of the current preset estimation cycle, and obtains the current forecast according to the related quantity of the measured data. The iteration parameter of the estimation period is set; the system error estimation value and the iteration parameter of the next preset estimation period are obtained according to the system error estimation value and the iteration parameter of the current preset estimation period and the measurement data of the next preset estimation period. This embodiment proposes a method of sampling at intervals, and then calculates the estimated value of the system error through an iterative correction method, which can improve the calculation efficiency and ensure the accuracy of the system error estimate and the fusion accuracy of the overall tracking system.

Description

technical field [0001] The invention relates to the technical field of system error estimation. More specifically, it relates to an error estimation method and system for a multi-sensor system. Background technique [0002] In the multi-radar network data processing, when the sensor platform is fixed and the sensor system error can be regarded as a fixed error when the regional climate, terrain and other factors are not considered, the existing system error estimation method can solve the problem under the premise of ensuring the estimation accuracy. The estimation algorithm based on the traditional generalized least squares (GLS) requires batch processing, which requires a large amount of calculation and poor real-time performance. However, for a target whose rate is not too high, when the sensor continuously observes the target for multiple moments and performs error estimation based on the sequence of corresponding position measurement values, the system error and the me...

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Problems solved by technology

[0002] In the multi-radar network data processing, when the sensor platform is fixed and the sensor system error can be regarded as a fixed error when the regional climate, terrain and other factors are not considered, the existing system error estimation method can solve the problem under the premise of ensuring the estimation accuracy. The estimation algorithm based on the traditional generalized least squares (GLS) requires batch processing, a large amount of calculation, and poor real-time performance.

However, for a target whose rate is not too high, when the sensor continuously observes the target for multiple moments and performs error estimation based on the sequence of corresponding position measurement values, the system error and the measurement data are relatively close due to the close distance between the position points at adjacent moments. The coefficient matrix in the discretized relational model of the system will lead to slow convergence of the system error estimation problem, and even show ill-conditioned, severe degradation of performance

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