An Improved Harmonic Suppression Method Based on Adaptive Compensation Algorithm for Monobit Receiver

• Published in: 2019 IEEE International Conference on Signal, Information and Data Processing (ICSIDP) pp. 1 - 6
• Main Authors: Yu, Muyao, Dong, Shengbo
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-12-2019
• Subjects: adaptive compensation algorithm; harmonic suppression; monobit receiver; sidelobe-to-maximum adjacent unit ratio criterion
• DOI: 10.1109/ICSIDP47821.2019.9172939

Monobit receiver is widely used in electronic warfare due to its large instantaneous receiving bandwidth, high sensitivity and high dynamic range. However, in the procedure of signal processing, monobit receiver generates high harmonics because of nonlinear quantization operations. These harmonics greatly reduce the instantaneous dynamic range (IDR) of the simultaneous signal, thereby reducing the performance of the monobit receiver. Meanwhile, the existing suppression methods are of great storage space and computational complexity. Aiming at the disadvantages in suppression efficiency, storage space, computational complexity and the balance between them of existing harmonic suppression methods, this paper proposes an improved harmonics suppression method based on adaptive compensation algorithm (ACA). Firstly, the peak frequency of signal spectrum is detected by monobit DFT, and the positions of the harmonics are located according to the peak frequency. Secondly, the sidelobe-to-maximum adjacent unit ratio (SMR) criterion is proposed, and each harmonic in compensation vector from the pre-stored compensation matrix is evaluated whether it needs to be compensated according to this criterion. Then, the adaptive compensation vector of each harmonic is used to suppress the harmonic components in the signal spectrum selectively. Finally, Updating the signal spectrum and performing the simultaneous signal detection based on proportional threshold. The simulation results show that the proposed method effectively suppresses the harmonics under different signal-to-noise ratios (SNRs) when compared to the traditional compensation algorithm and its improved algorithms. Meanwhile, the proposed method greatly improves IDR with less computational complexity and is easier to implement in engineering.