Object Detection Fault Identification Using Virtual Target Data
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Solution Overview
Problem
Conventional object detection systems face inaccuracies and design complexities due to the requirement for a virtual object to be within a specific range for fault identification, which limits their effectiveness during in-field operation and increases the risk of interference and real object detection inaccuracies.
Innovation Solution
An object detection system that uses processing circuitry to generate detection data by superimposing target data associated with a virtual object on echo data from a real object, allowing for fault identification beyond the range limit of the system, executed in a digital domain to reduce complexity and size, and enabling in-field fault detection and correction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a virtual object is used for fault identification in conventional object detection systems, then fault detection capability is provided, but the virtual object must be within a specific range which limits effectiveness during in-field operation and increases risk of interference and real object detection inaccuracies
Solution Approach 1:
The patent creates a digital copy of the expected echo signal (reference signal) that represents what the system should detect. This reference signal is generated based on predetermined parameters of the target object and is used to compare against actual received signals. By using a digital copy rather than requiring a physical virtual object within range, the system achieves fault detection without the limitations of physical object placement.
Solution Approach 2:
The patent replaces the mechanical requirement of placing a physical virtual object within detection range with a signal processing approach. Instead of relying on physical presence, the system uses digital signal generation, correlation, and comparison techniques to achieve the same fault detection function, thereby eliminating range limitations and interference risks.
2Reliability
If conventional methods are used for fault identification, then fault detection is possible, but design complexity and system size increase
Solution Approach 1:
The patent extracts the fault detection function from the main object detection workflow by implementing it as a separate signal processing stage. The reference signal generation and correlation process is implemented independently using existing processing circuitry, rather than integrating fault detection into the core detection algorithm. This modular approach reduces overall system complexity while maintaining detection capability.
Solution Approach 2:
The patent makes the existing processing circuitry perform multiple functions: it processes both normal object detection signals and fault detection reference signals using the same hardware resources. The correlation and comparison mechanisms serve dual purposes, eliminating the need for separate dedicated fault detection hardware and thereby reducing system size and complexity.
Data Source
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AI summary
An object detection system that includes a transceiver and processing circuitry is disclosed. The transceiver receives a chirp wave reflected from a real object that is in the vicinity of the object detection system, and generates echo data based on the received chirp wave. The processing circuitry generates detection data that includes the echo data and target data associated with a virtual object. The target data is generated to identify a fault in the object detection system while the object detection system is operating in-field. Further, the target data is indicative of predefined parameters of the virtual object. The processing circuitry then processes the detection data to detect the virtual object and extract various parameters of the detected virtual object. Further, the processing circuitry identifies the fault in the object detection system based on a comparison of the extracted parameters with the predefined parameters.