Vehicle Radar Ghost Target Filtering via Frame Bit Frequency
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Solution Overview
Problem
Radar sensors in vehicles often detect 'ghost targets' due to ambiguous signals outside their detection range, leading to unreliable target location information, which can cause malfunctions in autonomous driving systems.
Innovation Solution
An apparatus and method using a processor to determine whether a target detected by a radar sensor is a ghost target by analyzing the frequency differences between consecutive frames, allowing for correction of the target location and reducing the occurrence of ghost targets without additional components.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Length of stationary object
If radar sensor detects target using conventional methods, then detection range is extended, but ghost targets occur due to signal ambiguity
Solution Approach 1:
The patent applies dynamics by making the detection parameters adjustable and adaptive. The processor dynamically adjusts detection parameters such as pulse repetition frequency and antenna beam angle based on the movement characteristics of detected targets. This allows the system to optimize between detection range and accuracy in real-time, reducing ghost targets while maintaining extended detection capability.
Solution Approach 2:
The patent changes detection parameters dynamically based on target movement. The processor modifies pulse repetition frequency, antenna beam angle, and other parameters according to the calculated movement speed and position of targets. This parameter adaptation resolves the contradiction by adjusting the detection regime to match actual target characteristics, eliminating ghost targets when they are not present.
2Reliability
If additional components like absorbers are added to reduce ghost targets, then target detection reliability improves, but device complexity and manufacturing cost increase
Solution Approach 1:
The patent replaces physical/ mechanical solutions (such as absorbers or additional hardware components) with a signal processing and control-based solution. The processor analyzes received signals, calculates target movement characteristics, and adjusts detection parameters through software control. This substitution eliminates the need for additional physical components while achieving the same reliability improvement.
Solution Approach 2:
The system performs self-diagnosis and self-adjustment by analyzing its own detection signals. The processor identifies potential ghost targets through movement pattern analysis and automatically adjusts detection parameters to eliminate them. This self-service capability improves reliability without requiring external intervention or additional components.
3Measurement precision
If pulse repetition frequency is increased to improve detection accuracy, then target location precision improves, but detection range decreases
Solution Approach 1:
The patent makes pulse repetition frequency dynamic rather than fixed. The processor adjusts the pulse repetition frequency based on the calculated movement speed of detected targets. For stationary or slow-moving targets, a lower frequency maintains detection range, while for fast-moving targets, the frequency increases to improve location precision and track the target accurately.
Solution Approach 2:
The system performs preliminary detection at lower pulse repetition frequency to identify potential targets and calculate their movement characteristics. Based on this preliminary information, it pre-adjusts the pulse repetition frequency before detailed tracking begins. This preliminary action allows the system to optimize precision without sacrificing overall detection range.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Accurately determines and corrects the location of targets detected by radar sensors, enhancing detection performance and reducing manufacturing costs by eliminating the need for separate components like absorbers, thereby improving the reliability of autonomous systems.
Implementation Method 1
a radar sensor configured to track a target in motion
Data Source
AI summary
An apparatus including a radar sensor configured to track a target in motion, and a processor configured to determine a first bit frequency and a second bit frequency and determine based on the first bit frequency and the second bit frequency whether or not the target is a ghost target, in a case where a range gap between an n-th frame and an (n-1)-th frame is above a first value.