Main lobe jamming seriously affects the detection performance of airborne early warning radar.The joint processing of polarization-space has become an effective way to suppress the main lobe jamming.To avoid the main ...Main lobe jamming seriously affects the detection performance of airborne early warning radar.The joint processing of polarization-space has become an effective way to suppress the main lobe jamming.To avoid the main beam distortion and wave crest migration caused by the main lobe jamming in adaptive beamforming,a joint optimization algorithm based on adaptive polarization canceller(APC)and stochastic variance reduction gradient descent(SVRGD)is proposed.First,the polarization plane array structure and receiving signal model based on primary and auxiliary array cancellation are established,and an APC iterative algorithm model is constructed to calculate the optimal weight vector of the auxiliary channel.Second,based on the stochastic gradient descent principle,the variance reduction method is introduced to modify the gradient through internal and external iteration to reduce the variance of the stochastic gradient estimation,the airspace optimal weight vector is calculated and the equivalent weight vector is introduced to measure the beamforming effect.Third,by setting up a planar polarization array simulation scene,the performance of the algorithm against the interference of the main lobe and the side lobe is analyzed,and the effectiveness of the algorithm is verified under the condition of short snapshot number and certain signal to interference plus noise ratio.展开更多
In view of the obvious changes in color between the upper and lower leaf scar in sugarcane nodes,a method of simultaneous multi-nodes identification on a single sugarcane stem was proposed based on the analysis of gra...In view of the obvious changes in color between the upper and lower leaf scar in sugarcane nodes,a method of simultaneous multi-nodes identification on a single sugarcane stem was proposed based on the analysis of gradient characteristics of sugarcane images.In combination with image processing and machine vision recognition technology,two cameras were used to acquire different parts of sugarcane images,and the two images were integrated into a complete image of sugarcane by image mosaicking.The Sobel operator is used to calculate the gradient of the sugarcane image in a horizontal direction,and the gradient image is obtained.The sugarcane gradient image was scanned by a rectangular template with a width of 14 pixels and a step length of 12 pixels.The features of average gradient and variance gradient were used to identify sugarcane nodes for the first time.The experimental results showed that the recognition accuracy was 96.8952%,and there were fewer false detected sugarcane segments.The detection efficiency could be improved by detecting multi-nodes on a single sugarcane stem at the same time.展开更多
基金supported by the Aviation Science Foundation of China(20175596020)。
文摘Main lobe jamming seriously affects the detection performance of airborne early warning radar.The joint processing of polarization-space has become an effective way to suppress the main lobe jamming.To avoid the main beam distortion and wave crest migration caused by the main lobe jamming in adaptive beamforming,a joint optimization algorithm based on adaptive polarization canceller(APC)and stochastic variance reduction gradient descent(SVRGD)is proposed.First,the polarization plane array structure and receiving signal model based on primary and auxiliary array cancellation are established,and an APC iterative algorithm model is constructed to calculate the optimal weight vector of the auxiliary channel.Second,based on the stochastic gradient descent principle,the variance reduction method is introduced to modify the gradient through internal and external iteration to reduce the variance of the stochastic gradient estimation,the airspace optimal weight vector is calculated and the equivalent weight vector is introduced to measure the beamforming effect.Third,by setting up a planar polarization array simulation scene,the performance of the algorithm against the interference of the main lobe and the side lobe is analyzed,and the effectiveness of the algorithm is verified under the condition of short snapshot number and certain signal to interference plus noise ratio.
文摘In view of the obvious changes in color between the upper and lower leaf scar in sugarcane nodes,a method of simultaneous multi-nodes identification on a single sugarcane stem was proposed based on the analysis of gradient characteristics of sugarcane images.In combination with image processing and machine vision recognition technology,two cameras were used to acquire different parts of sugarcane images,and the two images were integrated into a complete image of sugarcane by image mosaicking.The Sobel operator is used to calculate the gradient of the sugarcane image in a horizontal direction,and the gradient image is obtained.The sugarcane gradient image was scanned by a rectangular template with a width of 14 pixels and a step length of 12 pixels.The features of average gradient and variance gradient were used to identify sugarcane nodes for the first time.The experimental results showed that the recognition accuracy was 96.8952%,and there were fewer false detected sugarcane segments.The detection efficiency could be improved by detecting multi-nodes on a single sugarcane stem at the same time.
