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Inverse synthetic aperture radar (ISAR) image distance unit selecting and cross-range scaling method

A unit selection and distance unit technology, applied in the field of radar, can solve the problems of angular velocity estimation error, frequency modulation error, difficulty in obtaining slope, etc.

Active Publication Date: 2013-02-27
XIDIAN UNIV
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Problems solved by technology

However, its shortcomings are also obvious. If the modulation frequency is not estimated accurately, it will be difficult to obtain the correct slope by least squares fitting, and the estimation of angular velocity will also be wrong, resulting in a large error in the result of lateral distance calibration.
In the measured data, due to the existence of various factors such as noise, target motion state, and the interaction of adjacent prominent points, the results of frequency modulation estimation are greatly affected. In fact, the frequency modulation estimated by many distance units is wrong.

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Embodiment Construction

[0050] refer to figure 1 , the specific implementation steps of the present invention are as follows:

[0051] Step 1, denote the radar pulse echo as S R (m, n), where Kuai is fast-time discrete sampling, m=1, 2,..., M, M is the number of distance units; n is slow-time discrete sampling, n=1, 2,..., N, N is pulse number.

[0052] Step 2, perform motion compensation on the radar pulse echo, and obtain the signal after motion compensation, denoted as S′ R (m, n).

[0053] (2a) Envelope alignment using neighbor correlation method.

[0054] (2a1) Denote the nth and n+1th adjacent echoes as S respectively R (m, n) and S R (m, n+1), their cross-correlation function is: R n，n+1 (k)=∑S R (m,n)S R (m-k, n+1); use the cross-correlation function R n，n+1 (k), calculate R n，n+1 (k) The delay value k corresponding to the peak value; when actually calculating the cross-correlation function, the time discrete value m is usually interpolated by 8 times;

[0055] (2a2) Using the del...

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Abstract

The invention discloses an inverse synthetic aperture radar (ISAR) image distance unit selecting and cross-range scaling method and mainly solves the problem that estimated errors of frequency modulation rates are large due to the fact that appropriate distance units are not selected by means of existing methods. The achievement process of the method includes reading radar pulse echo, subjecting radar echo data to motion compensation, selecting distance units where targets are located according to amplitude, selecting a required distance unit from the distance units where the targets are located according to various criterions, subjecting the selected distance unit to frequency modulation rate estimation by using local polynomial Fourier transform, performing secondary selection of a distance unit according to an area normalization criterion, and using a least square method for obtaining average for a plurality of times to obtain an angular speed estimation value so as to finish cross-range scaling of ISAR images by means of angular speeds. According to the ISAR image distance unit selecting and cross-range scaling method, accuracy of frequency modulation rate estimation is improved, and the method can be used for the cross-range scaling of the ISAR images.

Description

technical field [0001] The invention belongs to the technical field of radar, and relates to an ISAR horizontal calibration method, in particular, a range unit is selected by using various criteria, which can be used in target recognition based on ISAR images, and plays an important supporting role in feature extraction. Background technique [0002] ISAR horizontal calibration is a key technology involved in target recognition and classification based on ISAR imaging. The core of the horizontal calibration algorithm is to obtain the total rotation angle of the target relative to the radar line of sight within the imaging time, and all the horizontal calibration algorithms are also developed around this point. At present, horizontal calibration algorithms can be roughly divided into the following two categories: [0003] One is the calibration algorithm based on the image domain, including the image entropy method, the horizontal calibration algorithm based on the symmetric...

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Application Information

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IPC IPC(8): G01S13/89
Inventor 纠博刘宏伟王竞争王英华杜兰王鹏辉
Owner XIDIAN UNIV
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