A Dimensionality Reduction Sparse STAP Method and Device Based on Uncertain Prior Knowledge

A priori knowledge and dimensionality reduction technology, applied in measuring devices, radio wave reflection/re-radiation, instruments, etc., can solve problems such as high complexity, uncertain prior knowledge, and poor implementation of airborne radar clutter suppression , to achieve the effect of improving realizability and reducing computational complexity

Active Publication Date: 2021-08-31
SHENZHEN UNIV
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Problems solved by technology

[0004] The main purpose of the embodiments of the present invention is to provide a dimensionality reduction and sparse STAP method and device based on uncertain prior knowledge, which can at least solve the problem of the high complexity of the space-time adaptive processing algorithm adopted in the related technology, and the airborne The problem of poor implementation of radar clutter suppression

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  • A Dimensionality Reduction Sparse STAP Method and Device Based on Uncertain Prior Knowledge
  • A Dimensionality Reduction Sparse STAP Method and Device Based on Uncertain Prior Knowledge
  • A Dimensionality Reduction Sparse STAP Method and Device Based on Uncertain Prior Knowledge

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no. 1 example

[0033] In order to solve the unextensive adaptive processing algorithm in the related art, the implementation of poor realization in the inhibition of the airborne radar clutter, this embodiment proposes an uncertain prior knowledge. Designated STAP method, such as figure 1 The basic flow diagram of the drop-dimensional STAP method provided in this embodiment is shown, and the desired STAP method proposed in this embodiment includes the following steps:

[0034] Step 101, using the discrete Fourier transform to the radar reception signal to the radar, resulting in a hetero-whallar fortune reduction dimension measurement model.

[0035] In an alternative embodiment of this embodiment, see if figure 2 The flow schematic of the first-order degradation method, the implementation of step 101, specifically includes the steps of:

[0036] Step 201. Based on the reduction conversion matrix, the radar receive signal is reduced to the radar reception signal, and the interference component i...

no. 2 example

[0098] In order to more description of the contents of the present invention, the present embodiment illustrates the effects of different parameters to the present invention and the present invention in the sample data, SINR performance sparse recovery by simulation data.

[0099] In the simulation, the radar parameters are set as follows: Airborne Radar V p = 125m / s, h p = 4000m; D 0= 0.0625m and PRF = 4000Hz. Assuming clutter given distance into unit 361, a noise obeys each independent zero-mean complex Gaussian noise with variance satisfy a zero mean complex Gaussian distribution. The present embodiment is obtained by averaging the results of the simulation independent Monte Carlo experiment 500 times.

[0100] In the present embodiment, it is assumed coprime array has N = 6 sensors, which is coprime to N 1 = 2, N 2 = 3, a number of pulses of coherent processing interval (CPI) is M = 18, heteroaryl noise ratio CNR = 40dB, M e = 15, the number of training samples each experime...

no. 3 example

[0103] In order to solve high complexity adaptive processing algorithms air employed in the related art, the realizability in airborne radar clutter suppression poor technical problem, the present embodiment shows an embodiment based on a priori knowledge uncertainty dimensionality reduction sparse STAP device details, see Figure 11 , STAP sparse dimension reduction apparatus according to the present embodiment includes:

[0104] Order a dimension reduction module 1101, using the discrete Fourier transform for the received radar signal to a dimensionality reduction step to obtain a first-order noise reduction dimensional sparse measurement model;

[0105] Second order dimension reduction module 1102, for second-order and first-order dimension reduction to reduce clutter dimensional sparse measurement uncertainty model parameters a priori knowledge of the radar-dimensional matrix structure by reducing second order dimensionality reduction matrix of second order, resulting in a hybr...

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Abstract

According to a dimensionality reduction sparse STAP method and device based on uncertain prior knowledge disclosed in the embodiment of the present invention, discrete Fourier transform is used to perform first-order dimensionality reduction on radar received signals, and a clutter first-order dimensionality reduction sparse measurement model is obtained. Construct a second-order dimensionality reduction matrix based on the prior knowledge of uncertain radar parameters, and perform second-order dimensionality reduction on the clutter first-order dimensionality reduction sparse measurement model through the second-order dimensionality reduction matrix, and obtain the clutter second-order dimensionality reduction sparse measurement model ; Construct the clutter subspace optimization problem based on the clutter second-order dimensionality reduction sparse measurement model; solve the clutter subspace optimization problem to obtain the clutter subspace, and calculate the weight vector of the STAP filter through the clutter subspace. Through the implementation of the present invention, the second-order dimensionality reduction is performed on the clutter sparse measurement model, and the STAP filter weight vector is designed to avoid matrix inversion operation, which effectively reduces the computational complexity of filter design and improves the performance of airborne radar. Realization of clutter suppression.

Description

Technical field [0001] The present invention relates to the field of radar clutter suppression techniques, and more particularly to a reduction STAP method and apparatus based on uncertain prior knowledge. Background technique [0002] For airborne radar, Space-Time Adaptive Processing, STAP has always been an important technique for clutter suppression and target detection. It takes full use of the time domain information provided by the plurality of null channel information and the phase-free bursts provided by the phased array antenna, and improving the hybrid wave suppression through the airspace and the time domain two-dimensional adaptive filtering, and the traditional method is used only with Doppler. Dimension detection targets and only processes in the time-frequency domain. [0003] Compared to traditional moving target detection technology, the aerial adaptive processing technology has higher systemical freedom, more adaptability to handling background clutter, but the...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01S13/50G01S7/292G01S7/41G06F17/14G06F17/16
CPCG01S7/2923G01S7/414G01S13/50G06F17/14G06F17/16G01S7/356
Inventor 阳召成汪小叶刘海帆黄建军
Owner SHENZHEN UNIV
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