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Research in Sea Clutter Suppression Technology Based on Wavelet Neural Network

Author: WangChunPing
Tutor: ShenYan
School: Harbin Engineering University
Course: Applied Mathematics
Keywords: Sea Clutter Phase Space Reconstruction Wavelet Neural Network Suppression The average rate of compensation
CLC: TN957.3
Type: Master's thesis
Year: 2009
Downloads: 52
Quote: 1
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The sea clutter after radar signal radiation backscattered echo from the surface of the ocean , its presence seriously interferes with radar surface target detection and location tracking performance , making the radar in strong sea clutter and low probability of false alarm found that the ability of the target under the conditions greatly limited, can not even identify the target so if sea clutter interference to eliminate or reduce to a certain extent , it will be possible to improve the of Haiphong early warning radar target detection performance . , sea clutter suppression , including the sea under the sea clutter modeling and strong sea clutter target detection technology , is the current focus of research in the field of surface target detection and difficulty , has important practical significance to the design of radar systems , radar signal processing and surface target detection this wavelet neural network WNN (Wavelet Neural Network) method to study sea clutter inherent dynamics , the use of the trained wavelet neural network prediction and cancellation of the sea clutter , better clutter suppression effect . the main contents of the thesis is : based on the phase space reconstruction theory, the use of the GP ( Grassberger - Procaccia ) algorithm and the autocorrelation function to determine the embedding dimension m and embedding delay τ determine the correlation dimension method , resulting in a sea a sample of the clutter in the reconstruction phase space transition equation of state of the nonlinear system . establish WNN and error backpropagation network, namely BP (Back Propagation) network two predictive models with the inherent power of the sea clutter school characteristics prediction equation . measured IPIX (Intelligent Pixel-Processing) radar data network parameters training , the trained network is used to do single-step prediction when the error between the ideal value and the actual network output value reaches a specified accuracy requirements when the error becomes small amplitude signals , makes a strong amplitude the sea clutter conversion become weaker amplitude random noise signal , and can better detect the sea clutter weak target signal , sea clutter cancellation the purpose of suppression . compare the network model of sea clutter cancellation performance , define the average compensation rate , calculate the average rate of compensation for each network model in three kinds of norm . simulation results show that the the WNN average compensation rate larger than the BP network , that WNN rejection performance is superior to BP network .

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