Optimization of Multi-Subband Parallel and Signal Reconstruction for Remote Sensing Satellite Data Transmission

Abstract

The remote sensing satellite is developing toward high resolution, large data capacity, and fast transmission rate. The ground receiver is correspondingly required to have the high parallel to improve real-time reception and processing capabilities. In the frequency domain, the parallel processing of multiple subbands is achieved by dividing broadband into narrow bands. However, narrow-band subbands are reconstructed into broadband signals, which can lead to cross-subband distortion. It will affect the accuracy of high-resolution remote sensing images. In this article, the subband division and reconstruction framework is proposed by combining the analog filter with the digital filter. The phase calibration methods and digital filter optimization are proposed to improve the amplitude and phase consistency of the reconstructed signal. The simulation results show that the proposed amplitude consistency optimization method effectively reduces the reconstruction error within 0.001 dB. The proposed phase calibration method effectively reduces the bit error rate of the reconstructed signal. The maximum deviation is no more than 0.1%. Experiments have shown that the optimization method can reduce the distortion error of high-resolution remote sensing images.

Keywords

• Amplitude and phase consistency optimization
• high resolution
• multi-subbands parallel processing
• remote sensing satellites
• signal reconstruction