Intelligent radar sea clutter forecasting system and method based on differential evolution invasive weed optimization algorithm
An optimization algorithm and differential evolution technology, applied in radio wave measurement systems, instruments, etc., can solve problems such as insufficient intelligence and human factors
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Embodiment 1
[0106] refer to figure 1 , figure 2 , an intelligent radar sea clutter forecasting system based on the differential evolution invasive weed optimization algorithm, including a database 2 connected to the radar 1, and a host computer 3, the radar 1, the database 2 and the host computer 3 are connected in sequence, and the radar 1 pairs The detected sea area is irradiated, and the radar sea clutter data is stored in the database 2, and the upper computer 3 includes:
[0107] The data preprocessing module 4 is used for radar sea clutter data preprocessing, which is completed by the following process:
[0108]1) Collect N radar sea clutter echo signal amplitude x from the database i As training samples, i=1,...,N;
[0109] 2) Normalize the training samples to obtain the normalized amplitude
[0110]
[0111] Among them, minx represents the minimum value in the training sample, and maxx represents the maximum value in the training sample;
[0112] 3) Reconstruct the norm...
Embodiment 2
[0156] refer to figure 1 , figure 2 , an intelligent radar sea clutter prediction method based on differential evolution invasive weed optimization algorithm, the method includes the following steps:
[0157] (1) The radar irradiates the detected sea area, and stores the radar sea clutter data into the database;
[0158] (2) Collect N radar sea clutter echo signal amplitude x from the database i As training samples, i=1,...,N;
[0159] (3) Normalize the training samples to obtain the normalized amplitude
[0160]
[0161] Among them, minx represents the minimum value in the training sample, and maxx represents the maximum value in the training sample;
[0162] (4) Reconstruct the normalized training samples to obtain the input matrix X and the corresponding output matrix Y respectively:
[0163]
[0164]
[0165] Among them, D represents the reconstruction dimension, D is a natural number, and D
[0166] The robust foreca...
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