| Interference cognition is foundation and precondition of the intelligent anti-jam communication systems,it can real-time detect jamming holes of surrounding electromagnetic propagation environment, recognize jamming, estimate channel quality(SJNR) etc., and these results can provide the basis for the anti-jam decision systems to take anti-jam actions adaptively according to the surroudings. Based on the background, this dissertation describes the design and realization of the SJNR estimation module in the interference cognition system.Firstly, the paper presents the cyclostationary theory and cyclic autocorrelation function briefly. The cyclic autocorrelation functions of typical jamming and received signals in the defined channel model are deduced, and then the CS-SJNR algorithm of typical jamming are further deduced. In order to implement on FPGA, the CS-SJNR algorithm are simplified respectively in two different ways, the update rate and the resource consumption. Then the FPGA SJNR estimation link is designed and emulated, and the source of estimation error in high SJNR is explained.Based on CS-SJNR algorithm of the resource consumption version, the system compositions of the SJNR estimation link are designed. The compositions are grouped according to the function, such as the front-end preprocessing module, autocorrelation module, interweave module, power-computing module, FFT module, logarithmic-conversion module and periphery module. All modules have been emulated and verified. The hardware implementation platform, the interference cognition board, is also mentioned.At the end, the SJNR estimation module and interference detection module are integrated into the interference cognition system. The interface module is designed for the communicating between the interference cognition module and the upper control links. The FPGA link has been tested under different parameters configuration, mainly including the SJNR estimation module and interference detection module. |
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