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Autoregressive-model-based high range resolution profile radar target recognition method

A high-resolution range image and autoregressive model technology, applied in the field of target recognition, can solve the problems of increasing the recognition time, the total number of frames needs to be manually specified, and the recognition accuracy cannot be guaranteed, so as to achieve the effect of small demand

Active Publication Date: 2011-09-14
XIAN CETC XIDIAN UNIV RADAR TECH COLLABORATIVE INNOVATION INST CO LTD
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Problems solved by technology

But with this method, the total number of frames needs to be manually specified
If the number of frames is too many, it will increase the recognition time, which is not conducive to real-time recognition; if the number of frames is too small, the recognition accuracy cannot be guaranteed

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  • Autoregressive-model-based high range resolution profile radar target recognition method

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Embodiment Construction

[0018] refer to figure 1 , the specific implementation steps of the present invention are as follows:

[0019] Step 1. Calculate the spectrum magnitude signal corresponding to the high-resolution range image training samples.

[0020] Perform Fourier transform on the high-resolution range image training sample to obtain its frequency domain signal. In order to overcome the initial phase sensitivity of the frequency domain signal, perform a modulo operation on the frequency domain signal to obtain the corresponding spectrum amplitude of the high resolution range image training sample. Signal z = [z(1), z(2), ..., z(d)], where z(f) is the fth element of spectral magnitude signal z, .f = 1, 2, .. ., d, d denote the dimensions of the spectral magnitude signal z.

[0021] Step 2, use the autoregressive model to model the spectrum amplitude signal z, and extract the autoregressive coefficient vector as the identification feature.

[0022] The statistical properties of the high-re...

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Abstract

The invention provides an autoregressive-model-based high range resolution profile radar target recognition method. The method mainly solves the problems that the demand on training samples is high and the total number of frames of recognition features cannot be determined automatically in the conventional high range resolution profile radar target recognition technology. The method is implemented by the steps of: computing a frequency spectrum amplitude signal of a high range resolution profile training sample; modeling the frequency spectrum amplitude signal of the training sample by using an autoregressive model; computing a coefficient vector of the autoregressive model by using a Yule-Walker equation and using the coefficient vector as the recognition feature of the training sample; performing frame division on the recognition feature of the training sample by using a Gaussian mixture model; automatically determining the total number of the frames of the recognition features of the training sample and evaluating parameters of each frame by using a Bayesian Yin-Yang learning method; and extracting an autoregressive coefficient vector recognition feature of a test sample for recognition so as to obtain a recognition result. The autoregressive-model-based high range resolution profile radar target recognition method has the advantages that: the demand on the training samplesis low, the total number of the frames of the recognition features is determined automatically, and the method can be applied to radar target recognition.

Description

technical field [0001] The invention belongs to the technical field of radar and relates to a target identification method, which can be used to identify targets such as airplanes and vehicles. Background technique [0002] Radar target recognition is to use the radar echo signal of the target to realize the judgment of the target type. Broadband radar usually works in the optical region, where the target can be regarded as composed of a large number of scattered points with different intensities. The high-resolution range image is the vector sum of the echoes of each scattering point on the target body obtained by wideband radar signals. It reflects the distribution of scattering points on the target along the radar line of sight, contains important structural features of the target, and is widely used in the field of radar target recognition. [0003] Extracting recognition features from high-resolution range images is an important link in radar target recognition system...

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Application Information

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IPC IPC(8): G06K9/62G01S13/02G01S7/41
Inventor 刘宏伟王鹏辉戴奉周杜兰李彦兵王英华
Owner XIAN CETC XIDIAN UNIV RADAR TECH COLLABORATIVE INNOVATION INST CO LTD
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