Implementation of Real-Time Space Target Detection and Tracking Algorithm for Space-Based Surveillance

Abstract

Space-based target surveillance is important for aerospace safety. However, with the increasing complexity of the space environment, the stellar target and strong noise interference pose difficulties for space target detection. Simultaneously, it is hard to balance real-time processing with computational performance for the onboard processing platform owing to resource limitations. The heterogeneous multi-core architecture has corresponding processing capabilities, providing a hardware implementation platform with real-time and computational performance for space-based applications. This paper first developed a multi-stage joint detection and tracking model (MJDTM) for space targets in optical image sequences. This model combined an improved local contrast method and the Kalman filter to detect and track the potential targets and use differences in movement status to suppress the stellar targets. Then, a heterogeneous multi-core processing system based on a field-programmable gate array (FPGA) and digital signal processor (DSP) was established as the space-based image processing system. Finally, MJDTM was optimized and implemented on the above image processing system. The experiments conducted with simulated and actual image sequences examine the accuracy and efficiency of the MJDTM, which has a 95% detection probability while the false alarm rate is 10−4. According to the experimental results, the algorithm hardware implementation can detect targets in an image with 1024 × 1024 pixels in just 22.064 ms, which satisfies the real-time requirements of space-based surveillance.

A Space Target Detection Method Based on Spatial–Temporal Local Registration in Complicated Backgrounds

“…Space situational awareness (SSA) refers to observing, understanding, and predicting the physical location of organic and artificial objects in orbit around the Earth [2]. Investigating the detection and tracking of space targets using image data surrounding spacecraft acquired from space-based optical detection equipment is beneficial to advancing SSA technology and ensuring space environment safety [3,4].…”

“…By analyzing the grayscale difference of the central matching blocks between the target and clutter, the STDEM extracts the positive and negative grayscale peaks of the difference results to strengthen the target energy. 4.…”