Radar Clutter Localization Through Range-Doppler Vector Compression
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Solution Overview
Problem
Radar systems face challenges in effectively handling moving clutter, which can lead to false detections, inefficient resource utilization, and reduced operator trust due to increased false alarm rates, especially in environments with dynamic objects like moving tree branches or fans.
Innovation Solution
A radar device and method that compresses range-Doppler maps into one-dimensional vectors by combining Doppler bins for each range bin, using logical OR operations and weighted sums to identify and locate clutter sources, and employs a persistency filter to enhance target detection while reducing false alarms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the radar system processes all Doppler bins in the range-Doppler map to detect targets, then target detection capability is improved, but false detections from moving clutter increase
Solution Approach 1:
The patent segments the two-dimensional range-Doppler map into multiple one-dimensional vectors by dividing Doppler bins into groups. Each vector represents a specific range bin and contains Doppler information segmented into manageable groups. This segmentation allows selective processing of vectors to identify and filter clutter while preserving target detection capability.
Solution Approach 2:
The patent extracts clutter information by analyzing the distribution and characteristics of detected objects across multiple vectors. By identifying patterns specific to moving clutter (such as consistent presence across multiple frames at similar ranges), the system separates clutter from true targets, removing harmful false detections while maintaining reliable target detection.
2Object-generated harmful factors
If the radar system allocates processing resources to handle excessive moving clutter, then clutter mitigation is improved, but resource utilization efficiency deteriorates
Solution Approach 1:
Instead of processing the entire range-Doppler map with full clutter mitigation algorithms, the patent applies partial action by processing only selected vectors that are likely to contain clutter based on preliminary analysis. This selective processing reduces computational resource consumption while still achieving effective clutter mitigation in the most problematic areas.
Solution Approach 2:
The patent divides the processing task into segments by working with individual vectors rather than the complete two-dimensional map. This segmentation enables the system to allocate resources efficiently by focusing computational effort on specific vectors that require clutter mitigation, rather than uniformly processing all data, thereby improving resource utilization efficiency.
3Object-generated harmful factors
If the radar system uses traditional clutter mitigation techniques, then false alarm rate is reduced, but detection accuracy of actual targets deteriorates
Solution Approach 1:
The patent applies different processing qualities to different parts of the data by analyzing each vector individually and applying clutter mitigation only where needed. Instead of uniformly applying strong clutter suppression that might mask targets, the system uses local quality assessment to determine the appropriate level of processing for each vector, preserving target detection accuracy while reducing false alarms.
Solution Approach 2:
The patent incorporates feedback mechanisms by analyzing the results of vector processing and using this information to adjust subsequent clutter mitigation strategies. By monitoring detection patterns across multiple vectors and frames, the system provides feedback to refine its clutter identification and suppression, ensuring that actual targets are not mistakenly suppressed while false alarms are reduced.
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
Effectively identifies and localizes moving clutter, reducing false alarms and improving resource utilization by enhancing target detection accuracy and power efficiency in radar systems.
Implementation Method 1
Radar is a technology that uses radio waves to detect and locate objects. It operates by sending out radio waves and listening for any echoes that bounce back from objects
Implementation Method 2
it is known to obtain information on range, speed, and angles of objects, e.g. by performing multiple Fast Fourier Transforms (FFTs) on samples of radar mixer outputs
Implementation Method 3
Moving clutter in radar refers to unwanted radar returns from objects that are not the primary targets of interest but are moving and thus create Doppler shifts similar to those of true targets
Data Source
AI summary
In accordance with an embodiment, a method includes: determining, for at least one radar frame that includes a plurality of chirps emitted by a radar device, a range-Doppler map, wherein range bins along a first dimension of the range-Doppler map represent ranges relative to the radar device and Doppler bins along a second dimension of the range-Doppler map represent Doppler-shifts; for each of the range bins, combining the Doppler bins associated with the respective range bin to generate a vector indicating whether or not a target is detected in any of the Doppler bins associated with the respective range bin; and based on the vector, determining whether a source of clutter is present within a field of view of the radar device and a location of the source of clutter in the field of view.