Radar Echo Signal Superposition for Ranging Accuracy
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Solution Overview
Problem
The challenge is to enhance the signal-to-noise ratio of echo signals in radar systems, particularly when the distance between the radar and the target object is long or the target object has low reflectivity, leading to signal attenuation and noise dominance.
Innovation Solution
The proposed solution involves an echo signal processing method that determines a first pixel in the receiving field of view and multiple sampling point sets within the echo signal. It estimates distances based on these sampling points, determines cumulative receiving fields of view across multiple data frames, and superposes corresponding sampling point sets to enhance the signal-to-noise ratio.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the distance between the radar and target object is long or target reflectivity is low, then the optical signal energy is attenuated, but the signal-to-noise ratio deteriorates and ranging accuracy is reduced
Solution Approach 1:
The patent merges echo signals from multiple data frames through superposition processing. Specifically, it determines M cumulative receiving fields of view corresponding to M data frames, extracts sampling point sets from each frame, and superposes them to accumulate signal energy while suppressing random noise, thereby improving signal-to-noise ratio and ranging accuracy for weak echo signals
Solution Approach 2:
The patent performs preliminary estimation of target distance based on sampling point sets from the current data frame before superposition. This preliminary distance estimation guides the determination of cumulative receiving fields of view in previous data frames, enabling targeted signal accumulation from relevant temporal and spatial regions
2Reliability
If signal processing is performed on individual data frames independently, then processing complexity is low, but signal energy is insufficient and noise interference increases
Solution Approach 1:
The patent segments the signal processing into distinct functional modules: determining sampling point sets in current frame, estimating preliminary distance, determining cumulative receiving fields of view in M previous frames, extracting sampling point sets from each frame, and superposing them. This modular segmentation makes the complex inter-frame processing systematic and manageable
Solution Approach 2:
The patent extends signal processing from the spatial dimension (single data frame) to the temporal dimension (M cumulative data frames). By accumulating signals across multiple time frames and superposing them, the system exploits temporal redundancy to improve signal-to-noise ratio without proportionally increasing processing complexity
Data Source
AI summary
A method includes: determining, a first pixel in a receiving field of view of a radar and N sampling point sets in an echo signal corresponding to the first pixel; estimating an estimated distance between the radar and a target object based on each first sampling point set of the N sampling point sets, and determining, based on each estimated distance, M cumulative receiving fields of view in a one-to-one correspondence with M data frames; determining a second sampling point set in echo signals corresponding to Q neighboring pixels, and superposing each first sampling point set and the corresponding second sampling point set to obtain an echo signal that corresponds to the first pixel and that is obtained; and calculating an actual distance between the radar and the target object based on the echo signal obtained after superposition processing.