Factor analysis model-based high resolution range profile self-adaptive framing method

A technology of factor analysis model and distance image, applied in the field of signal recognition, can solve problems such as unreasonable, poor consideration of HRRP noise, and no noise consideration

Inactive Publication Date: 2017-08-15
NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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Problems solved by technology

However, this method is unreasonable. In the process of the target attitude changing continuously, the speed of change should directly affect the result of framing, that is to say, the frame size should be adaptively adjusted by the speed of the target attitude change.
For adaptive framing, predecessors also proposed a variety of methods, such as framing based on signal similarity, HRRP framing method based on subspace model, framing method based on probabilistic principal compone

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[0059] The present invention provides a one-dimensional range image adaptive framing method based on factor analysis model, the general flow chart is as follows figure 1 shown. The existing one-dimensional range image echo data of an aircraft are as follows: figure 2 As shown, in the actual situation, the echoes of different types of aircraft are different, and the same type of aircraft also has a large difference with the change of attitude. The 3 types of aircraft target flight trajectories used in the present invention are as follows: image 3 shown. The invention mainly solves the frame-by-frame recognition problem of this kind of one-dimensional echo signal. Include the following steps:

[0060] Training phase:

[0061] Step 1: For the training sample set X=[x 1 ,x 2 ,...,x M ], (x n ∈R 2m ) to extract its normalized frequency spectrum magnitude feature P=[p 1 ,p 2 ,...,p M ], (p n ∈R m ),like Figure 4 shown;

[0062] p i =|FFT(x i )|,i=1,2,..M (1)

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Abstract

The invention discloses a factor analysis model-based high resolution range profile self-adaptive framing method. The method includes the following steps that: the normalized spectrum amplitude feature of an actually measured high resolution range profile signal sample is extracted, the spectrum amplitude feature is evenly divided into small sub-frames; corresponding factor analysis models are established separately, the parameters of the models are calculated through using an EM iterative algorithm, so that the probability distribution of the sub-frames can be obtained; similarity measurement is performed on the sub-frame models through using the JS (Jensen-Shannon divergence) in the statistics, and adjacent sub-frames with high similarities are merged; and the operation of the second step and the third step is performed circularly until the Jensen-Shannon divergences between all the sub-frames are larger than a set threshold value, a frame merging process is terminated, and a framing result is outputted. According to the method of the invention, on the basis of the factor analysis models, and the Jensen-Shannon divergence is used to complete the merging of the frames; and as indicated by an experiment, the method of the invention enables a better framing effect and has higher recognition precision compared with a traditional uniform framing method and a newer probability principal component analysis model.

Description

technical field [0001] The invention belongs to the technical field of signal recognition, and relates to a method for framing one-dimensional radar signal recognition, in particular to a method for adaptively framing one-dimensional range images based on a factor analysis model, and in particular to a method for framing through a factor analysis model and JS Optimal Framing Method Combining Distance Measures. Background technique [0002] High-resolution one-dimensional range profile (HRRP) is a kind of target reflection signal based on broadband radar detection. It is the projection vector sum of target scattering point echoes in the direction of radar line of sight. It contains important structural information such as the size and shape of the target and Compared with SAR and ISAR images, it is easy to acquire and process, so it is widely used in the field of radar automatic target recognition, and it is the most promising radar target recognition method. [0003] Howeve...

Claims

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Application Information

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IPC IPC(8): G01S7/41
Inventor 戴为龙张弓张杨
Owner NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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