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Four-order cumulant sparse representation-based MIMO (multiple-input-multiple-output) radar direction of arrival estimation method under mutual coupling condition

A fourth-order cumulant and sparse representation technology, applied to radio wave measurement systems, instruments, etc., can solve problems such as estimation performance degradation

Inactive Publication Date: 2016-09-28
HARBIN ENG UNIV
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Problems solved by technology

However, when mutual coupling is considered or the noise is Gaussian colored noise, the estimation performance of the above method degrades

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  • Four-order cumulant sparse representation-based MIMO (multiple-input-multiple-output) radar direction of arrival estimation method under mutual coupling condition
  • Four-order cumulant sparse representation-based MIMO (multiple-input-multiple-output) radar direction of arrival estimation method under mutual coupling condition
  • Four-order cumulant sparse representation-based MIMO (multiple-input-multiple-output) radar direction of arrival estimation method under mutual coupling condition

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Embodiment 1

[0140] Step 1: Establishing the receiving signal model of the monostatic MIMO radar under the condition of unknown mutual coupling error, and using linear transformation to eliminate the influence of unknown mutual coupling according to the structural characteristics of the mutual coupling matrix.

[0141] Consider a narrow-band monostatic MIMO radar system. The transmitting array and the receiving array are composed of M and N antennas respectively, and the arrays are uniform linear arrays with a half-wavelength spatial spacing. In a monostatic MIMO radar the transmit and receive arrays are closely co-located, so they can be seen as having the same angle (ie, direction of arrival (DOA)) to a far-field target. The transmitting array uses M antennas to transmit M different narrow-band orthogonal waves with the same bandwidth and center frequency, assuming that the number of targets is P, θ p Denotes the DOA of the p-th target. In the case of K=k+1 non-zero mutual coupling coef...

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Abstract

The invention belongs to the monostatic MIMO (multiple-input-multiple-output) radar system technical field and relates to a four-order cumulant sparse representation-based MIMO (multiple-input-multiple-output) radar direction of arrival estimation method under a mutual coupling condition. The method of the invention comprises the following steps that: a transmitting array transmits mutually-orthogonal phase encoding signals, a receiving end carries out matched filtering on the phase encoding signals so as to obtain receiving data, and the influence of unknown mutual coupling is eliminated through linear transform based on the strap-shaped symmetric Toeplitz structures of the mutual coupling matrixes of the transmitting array and the receiving array; and a dimension reduction conversion matrix is constructed to carry out dimension reduction processing on mutual coupling-eliminated data, and a four-order cumulant matrix of a special form is constructed based on a new data matrix. According to the method of the invention, since the four-order cumulant technique and a weighted sparse representation framework are adopted, colored noises are successfully inhibited. The method of the invention can achieve accurate direction of arrival estimation under a Gaussian color noise condition, and has higher angular resolution and better angle estimation performance.

Description

technical field [0001] The invention belongs to the technical field of single base MIMO radar systems, and in particular relates to a method for estimating direction of arrival of MIMO radar waves based on fourth-order cumulant sparse representation under mutual coupling conditions. Background technique [0002] Multiple-input multiple-output (MIMO) radar is composed of a new array structure and emits mutually orthogonal waveforms. Compared with traditional phased array radars, it has many advantages such as higher resolution and better parameter identification, and is attracting more and more people. more attention. MIMO radar can be divided into two categories, statistical MIMO radar and coherent MIMO radar (IEEE Signal Processing Magazine, 2007, 24(5): 106-114). Statistical MIMO radar obtains spatial gain through a large antenna distance, while coherent MIMO radar forms a virtual array with a large aperture through a tight antenna distance to obtain higher spatial resolu...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01S7/02
CPCG01S7/02
Inventor 周卫东刘婧朱鹏翔宫文贺刘可
Owner HARBIN ENG UNIV
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