Multi-Timescale Doppler Radar Processing for Speed Resolution and Update Rate
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Solution Overview
Problem
Radar systems face challenges in efficiently detecting and tracking targets with varying velocities and distances while balancing detection power, resolution, and update rate, particularly in applications requiring both long detection ranges and fast update rates.
Innovation Solution
A multi-timescale Doppler processing approach is implemented, utilizing multiple Fast Fourier Transforms (FFTs) with varying processing sizes to process radar return data, allowing concurrent detection and tracking of targets using different timescales, merging detection data to avoid redundancy, and generating target data for appropriate mitigation actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single large processing size is used for Doppler processing, then detection power and speed resolution are improved, but update rate deteriorates
Solution Approach 1:
The patent divides the Doppler processing into multiple segments with different processing sizes (e.g., first processing size and second processing size). This segmentation allows the system to simultaneously perform processing with high speed resolution (using larger processing size) and maintain high update rate (using smaller processing size), resolving the contradiction between measurement precision and productivity.
2Productivity
If a single small processing size is used for Doppler processing, then update rate is improved, but detection power and speed resolution deteriorate
Solution Approach 1:
The patent segments the processing tasks into multiple parallel processing paths with different sizes. The smaller processing size path provides high update rate while the larger processing size path provides high speed resolution, and both results are merged to achieve both objectives simultaneously.
3Reliability
If multiple processing sizes are used concurrently, then both detection power and update rate are improved, but device complexity increases
Solution Approach 1:
The patent merges the results from multiple processing sizes into a unified detection output. By combining the detection data from different processing paths, the system achieves enhanced detection capability while managing complexity through a unified processing architecture that integrates multiple scales.
4Length of stationary object
If processing size is increased to detect distant targets, then detection range is improved, but computational resources required increase
Solution Approach 1:
The patent applies different processing sizes to different detection scenarios and target types. For distant targets requiring high detection power, the system uses larger processing sizes. For closer targets or when update rate is critical, it uses smaller processing sizes. This local quality approach optimizes computational resource usage based on specific detection needs.
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 enables the radar system to achieve high signal energy and fine speed resolution for distant targets while maintaining a high update rate for closer targets, enhancing detection and tracking capabilities across varying distances and velocities.
Implementation Method 1
performing a first plurality of Fast Fourier Transforms (FFTs) on a radar measurements matrix using a first processing size to provide a first plurality of FFT outputs
Data Source
AI summary
Multi-timescale Doppler processing and associated systems and methods are provided. In one example, a receiver receives radar return data, where the radar return data is associated with reflections, from a scene, of a plurality of transmitted radar signals. The radar return data is processed to obtain a plurality of sets of detection data, where each set of detection data of the plurality of sets of detection data is associated with a respective processing size. Target data associated with the scene is generated based at least in part on the plurality of sets of detection data. Related systems and methods are also provided.