Multi-Timescale Doppler Processing for Long-Range Radar Tracking
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Solution Overview
Problem
Radar systems face challenges in efficiently detecting targets at varying distances and velocities while balancing detection power, resolution, and update rate, particularly in applications requiring both long detection ranges and fast target tracking.
Innovation Solution
Implementing a multi-timescale Doppler processing approach that concurrently processes radar return data using multiple FFT sizes to generate detection data, allowing for simultaneous detection and tracking of targets at different ranges and velocities, combining results to achieve high signal energy, fine speed resolution, and fast update rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional single-timescale Doppler processing is used, then processing simplicity is maintained, but the system cannot simultaneously achieve long detection ranges, fine speed resolution, and fast update rates
Solution Approach 1:
The patent divides the Doppler processing into multiple timescales by performing FFT processing with different processing sizes (e.g., 4, 8, 16) concurrently. Each processing size corresponds to a different timescale, allowing the system to segment the detection task into multiple parallel processing streams that can be handled independently and simultaneously.
Solution Approach 2:
The patent introduces a new dimension of processing by implementing multi-timescale Doppler processing that operates concurrently across different processing sizes. This adds a temporal dimension to the traditional single-timescale processing, enabling the system to handle multiple detection requirements simultaneously without sequential processing.
2Measurement precision
If larger FFT processing size is used, then detection range and speed resolution are improved, but update rate decreases
Solution Approach 1:
The patent segments the Doppler processing into multiple parallel processing streams with different FFT sizes. While one stream uses larger processing size for high precision speed measurement, other streams use smaller processing sizes for faster update rates, allowing both requirements to be satisfied simultaneously through parallel processing.
Solution Approach 2:
The patent applies partial processing by using multiple processing sizes simultaneously - some for detailed analysis and others for rapid updates. This partial action approach allows the system to achieve high precision when needed while maintaining fast update rates through the parallel processing streams.
3Productivity
If smaller FFT processing size is used, then update rate increases, but detection range and speed resolution deteriorate
Solution Approach 1:
The patent segments the processing workload into multiple concurrent streams with different processing sizes. Smaller processing sizes handle fast update rate requirements, while larger processing sizes handle high precision requirements, allowing both objectives to be achieved simultaneously through parallel processing.
Solution Approach 2:
The patent adds a parallel processing dimension that allows simultaneous execution of multiple FFT processing sizes. This dimensional expansion enables the system to achieve both high update rates and high precision measurements by distributing different processing tasks across multiple concurrent streams.
4Adaptability or versatility
If multiple FFT sizes are processed concurrently, then detection capabilities across different ranges and velocities are enhanced, but processing complexity increases
Solution Approach 1:
The patent segments the complex multi-timescale processing into multiple independent but concurrent processing streams. Each stream handles a specific timescale with its own FFT processing, allowing the complexity to be distributed across parallel operations rather than concentrated in a single complex processing chain.
Solution Approach 2:
The patent introduces a concurrent processing dimension that allows multiple FFT sizes to be processed simultaneously rather than sequentially. This adds a temporal parallelism dimension that enhances detection capability while managing complexity through concurrent rather than sequential processing.
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
The system achieves enhanced detection capabilities with longer detection ranges and finer speed resolution for distant targets while maintaining the ability to track maneuvering targets with higher update rates, optimizing performance characteristics across different scenarios.
Implementation Method 1
A receiver for a radar system receives electromagnetic (EM) signals associated with a scene. The received EM signals are typically reflections of transmitted signals that impinge upon objects in the scene.
Implementation Method 2
Doppler processing is performed on the radar return data to generate sets of detection data. The processor performs a transform over a number of pulses to generate the sets of detection data.
Data Source
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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.