基于国产商用器件的星载智能目标检测技术

doi:10.7527/S1000-6893.2023.28860

Abstract

Abstract:

To address the problems of limited size and power consumption of the on-board computing platform， the hardware architecture of “FPGA+AI processor” is proposed， and the on-board image processing platform centering on the domestic commercial devices Fudan Micro JFM7K325T FPGA and Huawei Ascend310 AI processor is designed. Intelligent computing platform. To overcome the problem of high computational and storage costs for deep network algorithms， a ship target detection algorithm based on the lightweight remote sensing image is proposed， which effectively reduces the amount of computation and parameters while ensuring the detection accuracy. To solve the problem of slow computing in real-time deployment of neural network algorithms， we carry out quantization-aware training， calculation graph optimization of operator fusion， and multi-threaded parallel software design， which effectively improves real-time computing performance. The experimental results show that the power consumption of the system is less than 15 W， the detection accuracy of ships in remote sensing images reaches 0.908， the frame rate of 1 152×1 152 remote sensing image processing reaches 63.3 frames/s， and the frame rate of 4 096×5 120 large-format image processing reaches 3.17 frames/s. This paper realizes the real-time deployment of the deep learning algorithm of the domestically produced intelligent target detection platform， and explores the realization of an autonomous and controllable intelligent spaceborne front-end system.

Key words: on-board platform, remote sensing image, deep learning, domestic device, model optimization, ship detection

CLC Number:

V446⁺.4

Liqun CHEN, Xu ZOU, Lei ZHANG, Yingpan ZHU, Gang WANG, Jinyong CHEN. On⁃board intelligent target detection technology based on domestic commercial components[J]. Acta Aeronautica et Astronautica Sinica, 2023, 44(S2): 728860-728860.

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器件名	ZU9EG	XC7K325T	JFM7K325T（国产）
逻辑单元数量	599 500	326 080	326 080
内存大小/Kb	32 832	16 020	16 020
数字信号处理片数量	2 520	840	840

芯片名		Nvidia Jetson AGX XAVIER	Google TPU edge	Ascend 310
算力/TOPs		32	23	11
存储资源/ GB	LPDDR4	16	1	8
存储资源/ GB	eMMC	32	8
接口能力		MIPI CSI-2、USB、GMAC、PCIe、HDMI	PCIe/USB	PCIe、RGMII、USB
最大功耗/W		30	40	8
体积/（mm×mm）		105×105	48×48	15×15

架构名	传统架构	VPX	SpaceVPX
板级规范	无	3U/6U	3U/6U
单板功耗/W	≤20	≤80	≤80
总线协议	自定义	SRIO、PCIe、Ethernet	SRIO、PCIeEthernet、SpaceWire
冗余设计	自定义	无	双模冗余
扩展性	较差	较高	较高

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On⁃board intelligent target detection technology based on domestic commercial components

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