Missile Image Processing Architecture for Fast Target Tracking
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Solution Overview
Problem
Existing image processing systems in guided missiles face challenges in achieving high-resolution image processing efficiency, agility, and compact hardware design, particularly in detecting and tracking evasive targets while minimizing detection delays.
Innovation Solution
An image processing method utilizing a data bus to connect multiple image processing units, allowing flexible adaptation and optimized hardware use, with data fusion to generate steering commands for control wings, enabling longer processing times and efficient handling of computationally intensive tasks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution optics and powerful image processing hardware are used to detect distant targets, then target detection capability is improved, but hardware size and complexity increase
Solution Approach 1:
The image processing system is divided into multiple independent image processing units (IPUs), each capable of performing specific processing tasks. These units are connected via a data bus, allowing distributed processing that reduces the complexity burden on any single component while maintaining high-resolution processing capability.
Solution Approach 2:
The image processing units are designed to be multi-functional, capable of performing various image processing operations such as enhancement, filtering, and feature extraction. This universality allows a single IPU to handle multiple tasks, reducing the overall number of specialized components needed in the system.
2Speed
If sequential image processing steps are optimized for speed to track evasive targets, then tracking capability is improved, but processing time for each step decreases
Solution Approach 1:
The system performs preliminary image processing operations in parallel before final target detection and tracking. Multiple IPUs simultaneously perform different preprocessing tasks on incoming image data, preparing the data for subsequent rapid analysis and reducing the critical path time for target tracking decisions.
Solution Approach 2:
The image processing system operates continuously with pipelined processing stages, where different IPUs work on different frames simultaneously. This continuous operation ensures that processing is ongoing without idle time between frames, maximizing the utilization of processing resources while maintaining high tracking speed.
3Adaptability or versatility
If multiple image processing units are connected on a data bus for flexible adaptation, then adaptability is improved, but data bus contention and processing delays may increase
Solution Approach 1:
The data bus architecture implements dynamic arbitration and time-multiplexed access, where bus allocation changes based on current processing needs. High-priority processing units can obtain faster bus access when needed, while lower-priority units wait, thus adapting the system's time characteristics to the specific processing requirements without sacrificing flexibility.
Data Source
Figure 1~3
AI summary
The invention relates to an image processing method for determining steering commands for control fins (16) of a guided missile (2). To achieve high operational capability, it is proposed that a camera (6) records an environment, generates an image data set (B) from the recording and makes the image data set (B) available on a data bus (18), several image processing units (20, 22, 24) connected to the data bus (18) process data available on the data bus (18) and make their results available on the data bus (18), a data fusion (DF) combines the results associated with the image data set (B) into a main result (HE), and an autopilot (AP) calculates steering commands for the control fins (16) from the main result (HE).