Linear array expansion method

Abstract

The invention discloses a linear array expansion method, and belongs to the technical field of array beam forming. The method comprises the following steps: acquiring a received signal of a linear array; dividing the linear array into two sub-arrays according to odd and even array elements; calculating a received signal covariance matrix of the two sub-arrays formed by the odd and even array elements; constructing an extended receiving array signal according to the received signal covariance matrix; and performing beam forming and target detection by using a conventional beam forming technology or a minimum variance distortionless response beam forming technology. The problems of performance reduction and poor robustness under a low signal-to-noise ratio, non-circular symmetry requirementand limited application of a signal source signal, complexity and large calculation amount of the existing linear array expansion method are solved.

Description

technical field [0001] The invention relates to an array signal processing method, in particular to a line array array expansion method. Background technique [0002] Array signal processing technology is widely used in many military and civilian fields such as radar, communication, sonar, etc., and it is a focus issue in these fields. Signal-to-noise ratio is a key factor affecting the performance of array signal processing. For a given array configuration, the number of physical array elements and the array aperture are determined. How to improve the detection performance of weak targets under low signal-to-noise ratio is an urgent problem to be solved in engineering applications. It is an effective way to expand the aperture of the array and improve the detection performance of weak targets under low signal-to-noise ratio by using the array expansion technology to virtually increase the number of array elements. At present, the commonly used array expansion technologies...

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Problems solved by technology

[0003] The high-order cumulant method has good and stable array expansion characteristics, and according to the property that the high-order cumulant of the Gaussian signal is zero, it can suppress the Gaussian noise in the system, so that it can be used in different Gaussian noise environments. Good estimation performance, but this method has a large amount of calculation and there is a lot of redundant information. When the number of array elements increases, these redundant information may cause coupling between array elements; the interpolation transformation method realizes the array by increasing the number of array elements. However, it is difficult to determine the length of the sub-region and the step size of the interpolation transformation angle. How to balance the calculation amount and calculation accuracy of the algorithm is a major difficulty in the interpolation transformation method; the proposed method of reconstructing data based on the characteristics of the source and received signals In solving the problems of "angle sensitivity", "interpolation step size sensitivity" and large amount of calculation in the interpolation transformation method, but it is mainly applied to special two-dimensional arrays such as L-shaped arrays, how to apply this method to one-dimensional arrays The model needs to be studied; the currently commonly used one-dimensional linear array extension methods include the extension method based on the delay characteristics of the linear array and the linear array extension method based on the non-circular characteristics of the received signal. The former can achieve coherent signal while extending the array. The decoherence of the source, but the robustness is poor under the condition of low signal-to-noise ratio, and the latter requires the incident signal to have non-circular symmetry, which has limitations in application

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