Passive radar signal sorting association weight calculation method based on data mining

A passive radar and data mining technology, applied in computing, electrical digital data processing, other database retrieval and other directions, can solve the problems of large randomness of weight values, target splitting, failure of point-target association, etc. Effectiveness of credibility, improved science, improved applicability

Active Publication Date: 2015-11-04
THE 724TH RES INST OF CHINA SHIPBUILDING IND
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Problems solved by technology

Different R&D personnel have different experience values, the weight value is too random, and does not consider the data characteristics, to a certain extent, the error between the calculation result an

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  • Passive radar signal sorting association weight calculation method based on data mining
  • Passive radar signal sorting association weight calculation method based on data mining
  • Passive radar signal sorting association weight calculation method based on data mining

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Embodiment Construction

[0012] The process of the present invention is divided into:

[0013] Step 1 stores the passive radiation source information of T periods for each target k in K targets in a large sample; the data of each period includes the following characteristic parameters of the radiation source signal: direction of arrival DOA, pulse width PW, repetition period PRI, Signal carrier frequency RF, etc.;

[0014] Step 2: Establish a target signal sample matrix A for T periodic radiation source signal characteristic parameter indicators of a certain target k; Indicates the radiation source descriptor of the i-th period of the k-th target, where k=1,2,...,K, i=1,2,...,T, j=1,2,...,N respectively correspond to the direction of arrival DOA, pulse width PW, repetition period PRI, signal carrier frequency RF and other parameters;

[0015] Signal sample matrix A:

[0016] A = ED W ...

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Abstract

The invention relates to a passive radar signal sorting association weight calculation method based on data mining. The method comprises the following steps of: building a target signal sample matrix through large-sample storage of different-target different-period passive radar radiation source information on the basis of radiation source signal feature parameters such as the DOA (Direction of the Arrival), the PW (Pulse Width), the PRI (Pulse Recurrence Interval) and the RF (Radar Signal Carrier Frequency); adopting an improved information entropy method to obtain a parameter initial weight matrix by aiming at the matrix, and then performing weighted calculation to obtain a weight vector; and finally, performing association verification on the weight vector and providing a conflict resolution strategy. When the method provided by the invention is adopted, on the basis of large-sample data, the weight credibility can be enhanced; the improved information entropy method is used for performing association weight calculation; the scientificity of the weight can be improved; meanwhile, the inconformity is eliminated through obtaining the association weight on the basis of the initial weight matrix; and through the association verification, the applicability is improved. The method provides the method support for the passive radar signal sorting, and can be popularized to the field of radar data processing.

Description

technical field [0001] The invention relates to the field of passive radar signal sorting, in particular to a method for calculating the correlation weights between shipboard passive phased array radar signal sorting points and targets. Background technique [0002] Passive radar data processing includes two parts: signal sorting and target batching. Signal sorting is mainly to extract the pulse sequence belonging to the same radar radiation source from the interleaved, dense and complex pulse signal flow, and then calculate the pulse sequence so that Obtain radiation source parameters; target batching is the periodic processing of radiation source parameters output by signal sorting, including functional modules such as fusion, point and target association, filtering, and target initiation, among which the point and target correlation function module midpoint The calculation of the weight of each parameter of the target plays an important role in the success of the associat...

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Application Information

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IPC IPC(8): G06F17/30G01S7/02
CPCG01S7/02G06F16/90
Inventor 黄孝鹏韩向清李纪三匡华星
Owner THE 724TH RES INST OF CHINA SHIPBUILDING IND
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