| Emtter signal sorting is an important part of radar countermeasure. As the continuous deterioration of electronic environment, receiver possibly receives the forms of radar signal in all kinds of change, and the performance of accuracy sorting deteriorates seriously. At the same time, the performance of real time sorting is subjected to severe test. But the location of radar emitter is fixed, the DOA emitters would be the credible information for radar signal sorting and orientation. However, the intercept and capture of pluses usually lack the number of pluses categories. So radar emitter orientation information sorting belongs to the unsupervised clustering typically. There are important research meanings to research the unknown categories using the direction of arrival emitters for radar signal sorting with unsupervised clustering algorithm.In order to research the orientation information of emitters sorting in more detail, the paper firstly makes discussion of the method of phrase interferometer to extract orientation information. After derivation direction finding formulas based on the circular array, sum phrase and difference phrase information between baselines is changed and projected in the complex plane. The distribution law of projection points, which are ambiguous sum and difference phrase projection, is also detailed discussed. Then the method of sorting is proposed to solve ambiguous angles problem when direction finding. At the same time, the paper makes simulations and analysis for unwrapping ambiguity probability under different parameter, such as threshold radius.After acquisition the orientation information of emitters, the Fuzzy Adaptive Resonance Theory Neural Network as an unsupervised clustering algorithm is used in the paper. The Fuzzy ART Neural Network sorting algorithm is introduced. For the drawbacks and unreachable of algorithm when simulation and hardware implementation, the architecture of algorithm is improved. The method of updating weights is also proposed. The better sorting performance of reformulated algorithm is demonstrated by the computer simulation. At the same time, the reformulated algorithm is easy to be implementated with hardware.Finally, the paper makes FPGA implementation for the reformulated Fuzzy Adaptive Resonance Theory Neural Network algorithm. Based on the foundation of analysis parallel processing and word-length effect, the input module, the recall phrase mudule and the learning phrase mudule are ordered implementated with FPGA according to the architecture of algorithm. Synchronous Sequential Logic controller is made with state machine. Then all the modules can be ordered executed. According to the top layer module simulation, the results demonstrate that the accuracy rate with digital logical hardware is close to the accuracy rate with MATLAB software simulation. |
