Compressive Sensing Radar Imaging for Resolution and Complexity
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Solution Overview
Problem
Current radar systems face limitations in resolution due to the need for high sampling rates and large dynamic range A/D converters to handle wideband signals, which restricts the implementation of short duration pulses and increases costs.
Innovation Solution
The implementation of Compressive Sensing techniques allows for the recovery of radar reflectivity profiles from below Nyquist-rate sampled wave sequences, eliminating the need for matched filtering and reducing the required A/D converter bandwidth by utilizing a compressible representation of the radar scene and additional acquisition parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high sampling rate A/D converters are used to handle wideband signals, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent changes the sampling rate parameter from Nyquist rate to below-Nyquist rate, enabling the use of lower-rate A/D converters. Compressive sensing algorithms then reconstruct the high-resolution radar profile from these undersampled measurements, resolving the contradiction between measurement precision and device complexity
Solution Approach 2:
The patent replaces the traditional matched filtering mechanism with compressive sensing-based signal processing. Instead of using high-rate sampling followed by pulse compression, the system uses low-rate sampling followed by iterative reconstruction algorithms, substituting the mechanical sampling approach with a computational one
2Measurement precision
If short duration pulses are transmitted to achieve high resolution, then measurement precision is improved, but power requirements increase making implementation difficult
Solution Approach 1:
The patent applies preliminary modulation to the transmitted pulse (such as chirp or phase coding) before transmission. This allows the use of longer duration pulses with lower peak power while maintaining resolution through the compressive sensing reconstruction process, which exploits the structured nature of the modulated signal
Solution Approach 2:
The patent changes the pulse duration parameter from short to long duration, compensated by using modulated waveforms and compressive sensing reconstruction. This resolves the contradiction by allowing longer pulses (lower power) while maintaining resolution through signal processing
3Measurement precision
If pulse compression (matched filtering) is used to achieve high resolution, then measurement precision is improved, but the sampling rate requirements increase
Solution Approach 1:
The patent inverts the traditional processing order: instead of sampling at high rate then applying pulse compression, it samples at low rate then applies compressive sensing reconstruction. This inversion eliminates the need for high-rate sampling while achieving the same resolution through computational methods
Solution Approach 2:
The patent substitutes the matched filtering operation with iterative compressive sensing reconstruction algorithms. The computational reconstruction process replaces the traditional pulse compression mechanism, enabling resolution achievement without high-rate sampling
Data Source
AI summary
Method and apparatus for developing radar scene and target profiles based on Compressive Sensing concept. An outgoing radar waveform is transmitted in the direction of a radar target and the radar reflectivity profile is recovered from the received radar wave sequence using a compressible or sparse representation of the radar reflectivity profile in combination with knowledge of the outgoing wave form. In an exemplary embodiment the outgoing waveform is a pseudo noise sequence or a linear FM waveform.