Compressive Sensing Based Research On The Technology Of Eliminating Pulse Interference For Broadband Aeronautical Data Link

The multi-carrier transmission techniques based on Orthogonal Frequency Division Multiplexing(OFDM) will be used in the future broadband aeronautical data link system,which is designed as an inlay system in the L-band(890~1215MHz). However, as frequency resources are scarce, broadband aeronautical data link system has to coexist with the radio navigation systems already deployed in this band. Thus, how to eliminate interference of other L-band systems on the OFDM receiver becomes one of the key techniques on broadband aeronautical data link system application research.Because Distance Measuring Equipment(DME) system in L-band is the main interference source, the efficient algorithms based on the compressive sensing theory for eliminating DME pulse interference on the broadband aeronautical data link system are primarily discussed in this paper. Considering that DME signal has the block sparse feature,Block Sparse Bayesian Learning algorithm is selected to eliminate DME signal interference on the receiver of broadband aeronautical data link system.First, the mathematical models of broadband aeronautical OFDM system and DME system are built and the performance of Orthogonal Matching Pursuit algorithm and Pulse Blanking interference mitigating algorithm are analyzed and verified. Then, the principles and realization processes of BSBL algorithm are analyzed in detail.The Observation signal vectors are obtained by taking advantage of the intra-block correlation characteristic of pulse interference signals and the fact that the null sub-carriers do not transmit modulation symbols in the broadband aeronautical OFDM system. The learning rules of the sparse pulse signal statistical parameters are derived using EM algorithm. At last,pulse interference signals are reconstructed and eliminated from the receiver.The results of the simulation show that the position and amplitude of the pulse interference signals can be estimated effectively by using the interference mitigation method presented in this paper and the BER performance of the system has been significantly improved after the interference elimination.