Parallel accelerated computing architecture for dim target tracking on-board

IF 1.8 4区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Computational Intelligence Pub Date : 2023-09-24 DOI:10.1111/coin.12604
Jiyang Yu, Dan Huang, Wenjie Li, Xianjie Wang, Xiaolong Shi
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Abstract

The real-time tracking process of dim targets in space is mainly achieved through the correlation and prediction of dots after the detection and calculation process. The on-board calculation of the tracking needs to be completed in milliseconds, and it needs to reach the microsecond level at high frame rates. For real-time tracking of dim targets in space, it is necessary to achieve universal tracking calculation acceleration in response to different space regions and complex backgrounds, which poses high requirements for engineering implementation architecture. This paper designs a Kalman filter calculation based on digital logic parallel acceleration architecture for real-time solution of dim target tracking on-board. A unified architecture of Vector Processing Element (VPE) was established for the calculation of Kalman filtering matrix, and an array computing structure based on VPE was designed to decompose the entire filtering process and form a parallel pipelined data stream. The prediction errors under different fixed point bit widths were analyzed and deduced, and the guidance methods for selecting the optimal bit width based on the statistical results were provided. The entire design was engineered based on Xilinx's XC7K325T, resulting in an energy efficiency improvement compared to previous designs. The single iteration calculation time does not exceed 0.7 microseconds, which can meet the current high frame rate target tracking requirements. The effectiveness of this design has been verified through simulation of random trajectory data, which is consistent with the theoretical calculation error.

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用于机载昏暗目标跟踪的并行加速计算架构
空间昏暗目标的实时跟踪过程主要是通过检测和计算过程后的点关联和预测来实现的。跟踪的机载计算需要在毫秒级完成,在高帧速率下需要达到微秒级。对于空间昏暗目标的实时跟踪,需要针对不同的空间区域和复杂背景实现通用的跟踪计算加速,这对工程实现架构提出了很高的要求。本文设计了一种基于数字逻辑并行加速架构的卡尔曼滤波计算,用于实时解决星载昏暗目标跟踪问题。针对卡尔曼滤波矩阵的计算,建立了统一的矢量处理单元(VPE)架构,并设计了基于 VPE 的阵列计算结构,将整个滤波过程进行分解,形成并行流水线数据流。分析和推导了不同定点位宽下的预测误差,并根据统计结果提供了选择最佳位宽的指导方法。整个设计基于 Xilinx 的 XC7K325T,与以前的设计相比提高了能效。单次迭代计算时间不超过 0.7 微秒,可以满足当前高帧率目标跟踪的要求。通过模拟随机轨迹数据,验证了该设计的有效性,与理论计算误差相符。
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来源期刊
Computational Intelligence
Computational Intelligence 工程技术-计算机:人工智能
CiteScore
6.90
自引率
3.60%
发文量
65
审稿时长
>12 weeks
期刊介绍: This leading international journal promotes and stimulates research in the field of artificial intelligence (AI). Covering a wide range of issues - from the tools and languages of AI to its philosophical implications - Computational Intelligence provides a vigorous forum for the publication of both experimental and theoretical research, as well as surveys and impact studies. The journal is designed to meet the needs of a wide range of AI workers in academic and industrial research.
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