General purpose graphic processing unit implementation of adaptive pulse compression algorithms

Abstract

, "General purpose graphic processing unit implementation of adaptive pulse compression algorithms," J. Appl. Remote Sens. 11(3), 035009 (2017), doi: 10.1117/1.JRS.11.035009. Abstract. This study introduces a practical approach to implement real-time signal processing algorithms for general surveillance radar based on NVIDIA graphical processing units (GPUs). The pulse compression algorithms are implemented using compute unified device architecture (CUDA) libraries such as CUDA basic linear algebra subroutines and CUDA fast Fourier transform library, which are adopted from open source libraries and optimized for the NVIDIA GPUs. For more advanced, adaptive processing algorithms such as adaptive pulse compression, customized kernel optimization is needed and investigated. A statistical optimization approach is developed for this purpose without needing much knowledge of the physical configurations of the kernels. It was found that the kernel optimization approach can significantly improve the performance. Benchmark performance is compared with the CPU performance in terms of processing accelerations. The proposed implementation framework can be used in various radar systems including ground-based phased array radar, airborne sense and avoid radar, and aerospace surveillance radar.

Error Modeling and Accuracy Analysis of Shipborne Radar Measurement Signal Processing

“…The ship will have pitch, roll, heave and heading change at sea, and the change of attitude has a great influence on the measurement results of radar [3,4] . Therefore, shipborne radar needs a stable platform to compensate the influence of carrier attitude on radar measurement [5,6] . The traditional way is to set up the radar on the mechanical stabilization turntable [7,8] , and the stabilization turntable has a set of servo drive devices on the pitch axis and the roll axis respectively [9,10] .…”