Selection method for localization node without priori measurement error
In response to the problem of existing localization node selection algorithms relying on prior measurement error,this paper studies a passive localization node selection method for time difference of arrival and frequency difference of arrival(TDOA-FDOA)that does not rely on prior measurement error.This method takes the covariance of the target estimation error in the two-stage weighted least squares(TSWLS)localization algorithm as the objective function.Given the number of available positioning nodes,a minimum estimation error optimization problem with constraints on the objective function is constructed by introducing a set of boolean variables.The non-convex problem is transformed into a semi definite programming semi-definite programming(SDP)problem through semi-definite relaxation(SDR)technique for solution.Based on the characteristics of the minimization problem,the proposed algorithm does not rely on prior measurement error.The simulation results show that there is no significant difference in positioning performance between methods that do not rely on measurement error and exhaustive search methods;Compared to exhaustive search algorithms,the proposed method has lower complexity and better real-time performance.The simulation results further demonstrate the necessity of timely adjusting the combination of positioning nodes in the process of locating moving targets.
passive localizationtime difference of arrival(TOOA)frequency difference of arrival(FDOA)semi-definite programming(SDP)node selection optimization
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