Research On Anti Jamming Algorithm Based On Confidence Probability Mapping

Nowadays, electronic warfare plays a very important role in the modern warfare. Jamming and anti-jamming technology is in the core position of the electronic warfare. For battlefield communication systems, how to deal with interference of the enemy is the key to the successful completion of the battlefield communication task. In order to achieve the purpose of anti-jamming, most existing jamming signal processing technology use certain method to eliminate or weaken the jamming signal. In these interference processing techniques, the time domain interference processing technology is poor in real time, and can not cope with the fast changing jamming signal. For the frequency domain interference processing technology, computational complexity is high and the hardware implementation is difficult. In soft decoding of convolutional codes, the soft decoder uses the confidence information given by quantizer to make more accurate decoding, but the anti-jamming ability of convolutional codes is not will. In this thesis, a new anti-jamming algorithm based on confidence probability mapping of convolutional codes is proposed.The first chapter introduces the research background, after that, summarizes the development of anti-jamming technology and the shortcoming of existing processing technology of jamming. And then this chapter puts forward the significance and value of this thesis’s topic, finally gives the work arrangement of this thesis.In the second chapter, it mainly analyzes the encoder structure of convolutional codes, the image and algebra presentation of the convolutional codes, the distance property of convolutional codes and the maximum likelihood decoding of the convolutional codes. Last part of the second chapter introduces the classification of jamming signal, the mathematical model of single tone jamming signal and LFM jamming signal.In the third chapter, from the view of signal confidence information, the front end quantizer of the soft decision decoder of convolutional codes is analyzed, and accordingly the confidence probability mapping function is established. Then after the analysis of the performance of convolutional codes, the bit error performance of the convolutional code and confidence probability mapping function, the anti-jamming algorithm based on the confidence probability mapping is transformed into the problem of the optimal quantization. After that, the conditional transition probability density function of the channel is derived in various channel conditions, at the end of this chapter, the source of error is analyzed.In chapter four,2 bit uniform optimal quantization and 3 bit uniform optimal quantization are simulated and analyzed to verify the correctness of the algorithm in various channel conditions. Finally, the performance curves of this algorithm in uniform quantization are given. Then conclusions are given. In the last part of this chapter, the non-uniform quantization is explored and the performance curves are given.The fifth chapter summarizes the work of this thesis, gives the conclusion, and gives the next step of this algorithm research.