3 results about "Hadamard matrix" patented technology

The application discloses a kind of ghost imaging reconstruction and classification method and equipment based on hybrid network, belong to the field of computational imaging technology, will be based on Hadamard matrix generation light speckle sequence formed by fixed light speckle sequence;Then, based on this light speckle sequence sampling expanded MNIST data set, generate light intensity sequence, light speckle sequence data;Then, construct and train GRU-CNN network model;Finally, using the model trained to calculate correlation imaging reconstruction and target identification classification.The conventional ghost imaging technique is often faced with the problem of poor image quality under low sampling conditions.In order to solve this problem, the application proposes a GRU-CNN network (GCGI) model combined with deep learning, which can efficiently reconstruct high-quality images and accurately identify and classify targets under very low sampling rates by fusing light intensity sequence and light speckle information, and has strong practical value.

The present application belongs to the technical field of calibration of phased array radar, and relates to a two-stage grouping asynchronous rotating electric vector radar array antenna calibration method, and the specific process is as follows: an attenuator and a phase shifter are configured to each element channel of the array antenna to be measured, and signals received by all channels are synthesized through a power divider; the phased array radar to be measured is equally grouped by channel number in a first stage; a grouping matrix is constructed based on a Hadamard matrix, and the channels grouped in the first stage are divided into rotating groups and fixed groups according to elements in the grouping matrix; a phase shift matrix for phase shift measurement of each row in different grouping matrices is constructed based on a discrete Fourier transform matrix with an order of N, and phase shift is performed; linear equations are constructed according to measurement results and solved, and the ambiguity coefficient, the amplitude of each channel and the phase difference between each channel are obtained, and each field normalization amplitude and phase is solved; amplitude and phase compensation of the channels is completed based on each field normalization amplitude and phase, and finally the amplitude and phase of all channels are consistent.

The application discloses a signal fluctuation extraction method combining a Hadamard matrix and mathematical morphology, and comprises the following steps: determining the order m of the Hadamard matrix and the specific number l of rows to be selected according to signal characteristics and sampling accuracy; taking the lth row of the selected Hadamard matrix as a structure element g to perform mathematical morphology operation on an input signal f to obtain a signal fluctuation part and complete the extraction operation. According to the application, a certain row in the Hadamard matrix is selected as the structure element according to signal characteristics, and the order of the matrix is determined; the characteristics that the Hadamard matrix only takes values of 1 and -1 are utilized; the fundamental component in the signal is suppressed through the morphological operation; and the fluctuation part is extracted. The orthogonality of the Hadamard matrix is fully utilized, the Hadamard matrix is used as the structure element for the morphological transformation, the signal can be processed simply and quickly, and the characteristic information is extracted. The application of the mathematical morphology can accurately analyze the signal in the time domain.