FMCW Radar Interference Mitigation via Velocity-Direction Histogram
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Solution Overview
Problem
FMCW radar systems in autonomous vehicles face challenges in distinguishing between genuine target reflections and erroneous detections caused by interfering radar signals, leading to incorrect target identification and potential safety issues.
Innovation Solution
The implementation of a velocity-direction histogram analysis, where detections are assigned to bins based on computed velocity and direction values, allowing for the identification and filtering of interfering signals by comparing detection counts against predefined thresholds, thereby distinguishing between genuine and interfering signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If interference nulling is used to detect FMCW chirps emitted by interferers, then interfering signals can be detected, but information from ADC output is dismissed and it becomes difficult to detect interfering signals in raw data stream
Solution Approach 1:
The patent extracts interfering signals from the raw data stream by analyzing ADC output data without discarding it. The processing circuitry identifies interfering signals by examining the characteristics of downmixed signals while preserving all original ADC output information for further analysis, thus detecting interferers without losing valuable data.
Solution Approach 2:
The patent introduces an intermediary analysis step where the processing circuitry examines the downmixed signal characteristics between the ADC output and final detection. This intermediary analysis allows identification of interfering signals through their distinct properties (such as constant frequency after downmixing) while maintaining access to all original ADC information.
2Measurement precision
If modulation parameters are randomly varied to avoid interfering signals, then detection accuracy improves, but additional circuitry and processing complexities are introduced
Solution Approach 1:
Instead of randomly varying modulation parameters, the patent changes the analysis parameter by examining the frequency characteristics of downmixed signals. The processing circuitry identifies interfering signals by detecting their constant frequency property after downmixing with the local oscillator, achieving improved detection accuracy without modifying the original FMCW chirp parameters or adding complex modulation variation circuitry.
3Reliability
If frequency hopping is employed to avoid interfering signals, then interfering signal detection is avoided, but additional processing complexities and bandwidth requirements are introduced
Solution Approach 1:
The patent creates a virtual frequency domain representation by downmixing the received signal with the local oscillator. This copying of the signal to baseband allows the processing circuitry to identify interfering signals through their distinctive constant frequency characteristic without requiring actual frequency hopping or additional bandwidth, thus avoiding interferers through intelligent signal analysis rather than frequency avoidance.
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
This approach effectively filters out detections caused by interfering signals, improving the accuracy of target identification and reducing false positives, enhancing the reliability of radar systems in autonomous vehicles.
Implementation Method 1
A radar system is configured to generate detections within respective temporal detections windows... An example type of radar system is a frequency-modulated continuous-wave (FMCW) radar system, where an FMCW radar system is configured to transmit an FMCW signal that includes FMCW chirps into the environment
Implementation Method 2
when a detected radar signal includes a reflection of an FMCW chirp off of a target, the radar system outputs a detection based upon a difference between a frequency of the LO and a frequency of the detected radar signal
Implementation Method 3
The radar system generates detections based upon the detected radar signal being downmixed with a local oscillator (LO)... each detection is generated based upon a downmixed signal that is created by downmixing the LO with a radar signal detected by the radar system
Data Source
AI summary
Technologies are described herein that are configured to identity detections output by a frequency-modulated continuous-wave (FMCW) radar system that are caused by an interfering signal. The detections are detected as being caused by an interferer based upon numbers of detections assigned to bins in a velocity-direction histogram.