Method for increasing imaging quality of sparse constrained ghost radar

A sparse constraint, radar imaging technology, applied in the field of compressed sensing, can solve the problems of limited light source intensity, high computational complexity, slow reconstruction speed, etc., to achieve the effect of improving imaging quality and low computational complexity

Inactive Publication Date: 2017-05-17
NANJING UNIV OF SCI & TECH
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Problems solved by technology

For example, the method proposed by Shapiro et al. (Shapiro, Jeffrey H. "Computational ghost imaging." Physical Review A78.6(2008): 061802.) using micro-mirror arrays instead of rotating frosted glass, but this method greatly limits the light source Intensity, which limits the detection distance
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  • Method for increasing imaging quality of sparse constrained ghost radar
  • Method for increasing imaging quality of sparse constrained ghost radar
  • Method for increasing imaging quality of sparse constrained ghost radar

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Embodiment

[0046] The method for improving the imaging quality of the sparse constrained ghost radar in the present invention has the following steps:

[0047] first step, such as figure 1 and figure 2 As shown, for the 64×64 experimental target image, according to the 1500 speckles generated by the rotating ground glass, the CCD camera is used to detect and reduce the dimension to a 64×64 speckle image frame by frame. At the same time, the single-pixel detector 1500 measurements were collected; the speckle image and the corresponding measurement values ​​were subjected to a second-order correlation operation, Δ(k)=-, get the second-order correlation of the measured value and the second-order correlation of the sampling matrix respectively.

[0048] The second step is to use the existing CVX convex optimization toolkit of Matlab software to express the second-order correlation between the measurement value and the measurement matrix in the form of a matrix, and use the existing matchin...

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Abstract

The invention discloses a method for increasing imaging quality of a sparse constrained ghost radar. The method includes the following steps: firstly using the measured values of the sparse constrained ghost radar and the correlation of a measurement matrix in a spatial domain, by conducting spatial second order operation, and constructing a new measurement matrix which meets orthogonal constraints so as to suppress influence on image reconstruction imposed by the non-orthogonality of the measurement matrix; and using the new measurement matrix which meets orthogonal constraints and is obtained from the first step, based on existed sparse constrained conditions, converting the new measurement matrix to the problem of convex optimization, and when the conditions of convergence and stability are met, finding a L-norm-based optimal solution by the existed algorithm which matches tracking so as to increase the imaging quality of the sparse constrained ghost radar. According to the invention, the method effectively suppresses the influence on the sparse constrained ghost radar imposed by reconstruction noise and increases the imaging quality of the sparse constrained ghost radar.

Description

technical field [0001] The invention belongs to the technical field of compressed sensing, in particular to a method for improving the imaging quality of sparse constrained ghost radar. Background technique [0002] Sparse constrained ghost radar is a kind of speckle (measurement matrix) that uses rotating ground glass to produce speckle (measurement matrix) that satisfies the binomial distribution to illuminate the target. It can achieve high resolution through nonlinear constrained reconstruction at a condition much lower than the Nyquist sampling rate. High-speed image reconstruction is widely used in imaging radar technology in remote sensing, complex environment imaging and other fields. [0003] However, the binomial distribution speckle produced by the sparsely constrained ghost radar does not satisfy the orthogonality constraint, which significantly restricts the target reconstruction. At present, for the reconstruction image degradation caused by the sparse constra...

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Application Information

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IPC IPC(8): G01S13/89
CPCG01S13/89
Inventor 余敏邹云浩何伟基冒添逸陈钱顾国华张闻文钱惟贤隋修宝任侃路东明于雪莲
Owner NANJING UNIV OF SCI & TECH
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