Noise subspace estimation method based on application of sliding window determination in MWF

A technology of noise subspace and interference subspace, applied in the field of signal processing, can solve the problems of changing with the environment, difficult to find, and the difference of the residual variance of the received signal is not obvious, so as to avoid the logarithmic operation and facilitate the realization.

Active Publication Date: 2018-12-28
NAT UNIV OF DEFENSE TECH
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Problems solved by technology

Using the classic MWF to reduce the dimensionality of the space-time two-dimensional pattern anti-interference processing will make it difficult to estimate the optimal subspace dimension accurately. There are two reasons: 1. The noise changes with the environment, and it is difficult to accurately estimate the interference subspace with a fixed threshold Dimension; 2. Because each step of the MWF extracts the interference component according to the maximum correlation with the received signal vector, the variance of the

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  • Noise subspace estimation method based on application of sliding window determination in MWF
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  • Noise subspace estimation method based on application of sliding window determination in MWF

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[0028] Below in conjunction with accompanying drawing, the present invention is described in detail:

[0029] The main link of space-time two-dimensional processing is weight calculation, with image 3 It is a noise subspace estimation method based on the MWF theory which uses the sliding window to determine the order. Use this method to complete the calculation of the optimal weight, such as figure 1 The part identified by "w" in the . The steps of using this method for space-time two-dimensional processing are as follows:

[0030] S1. Transform the problem of anti-interference processing into Wiener filtering mode: pass the received signal vector through the generalized sidelobe canceller to obtain the expected signal of the upper branch, denoted as d 0 (n), lower branch x 0 (n) is the signal vector to be processed, as attached figure 1 , forming the pattern of the Wiener filter.

[0031] S2. Roughly estimate the dimension of the interference subspace: according to the...

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Abstract

The invention relates to a noise subspace estimation method based on the application of sliding window determination in MWF. In the method, according to the characteristics of MWF and in combination with the maximum eigenvalue operation of a small matrix, a method for order determination by using a sliding window is provided, so that a noise subspace can be estimated robustly, and an optimal signal to interference plus noise ratio is obtained more stably. By adoption of the method, the interference subspace decomposition can be more accurate and reliable so as to obtain a better anti-interference effect.

Description

technical field [0001] The invention mainly relates to the field of signal processing, in particular to a noise subspace decomposition method using sliding window judgment based on MWF. Background technique [0002] The power of the navigation signal received by the earth's surface is very small, taking GPS as an example, it is about 21dB lower than the thermal noise of the receiver. When subject to man-made interference, the received signal is difficult to recover. Using the antenna array and performing time delay expansion to form a space-time two-dimensional pattern can greatly increase the degree of freedom and enhance the anti-interference ability. Assuming that the number of array elements is M and the number of time delays is N, the received data X is an MN×1-dimensional vector, and its covariance matrix R x =E{XX H}, is an MN×MN dimensional matrix, and its optimal processing operation is about O((MN) 3 ), with the increase of the dimension of space-time processin...

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Application Information

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IPC IPC(8): G01S19/21
CPCG01S19/21
Inventor 周柱张茂军刘煜
Owner NAT UNIV OF DEFENSE TECH
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