Estimation method and apparatus for direct position of data domain of mobile communication signal source

Abstract

The present invention relates to an estimation method and apparatus for a direct position of a data domain of a mobile communication signal source. The method comprises the steps of collecting, by each observation station, original observation data; performing bottom layer data fusion on collected original observation data, and generating a direct positioning model comprising position information; building, based on a stochastic matrix asymptotic distribution theory, a cost function comprising a noise subspace and a signal subspace; and resolving the cost function, and outputting a final target position. By combining the original observation data of each observation station, thorough bottom layer fusion is performed on the received data, so as to reduce position information loss and improve the positioning precision. A brand-new cost function comprising both the signal subspace and the noise subspace is built based on the stochastic matrix asymptotic distribution theory, so that the signal source identification capability of the direct position determination is stronger in poor wireless communication environments such as low signal to noise ratio and fewer samples. Simulation experiments prove that the positioning precision is higher, and the performance is more stable.

Description

technical field [0001] The invention belongs to the technical field of wireless signal source position estimation in mobile communication, and in particular relates to a method and a device for directly estimating the position of a mobile communication signal source data domain. Background technique [0002] Passive positioning has good concealment, is not easy to be interfered and attacked, and is widely used in military and civil affairs. The traditional passive positioning system mainly uses a two-step positioning method, that is, firstly estimate the position parameters of the target (DOA, TOA, FDOA, etc.), and then use the estimated position parameters to establish a position equation to complete the solution of the target position. This makes the parameter estimation and position calculation separated, the loss of position information is inevitable in the process of data processing, and it is impossible to ensure that the measured parameters match the real position of ...

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Problems solved by technology

However, the algorithm fails to make full use of the original observation data of each station, and only the noise subspace is used in the cost function instead of the signal subspace, resulting in the loss of positioning accuracy and the decrease of signal source resolution.

Although the existing multi-site subspace data fusion direct positi

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