Cognitive Radar Processor De-noising Below-Noise Signals
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Solution Overview
Problem
Current radar systems face challenges in detecting targets over ultra-wide bandwidths due to high power requirements, computational complexity, and size, weight, and power constraints, particularly in de-noising below-noise radio frequency signals, which limits their operational range and real-time processing capabilities.
Innovation Solution
A cognitive radar processor utilizing a time-varying reservoir computer with a delay embedding module and weight adaptation module, capable of de-noising signals using predictive filtering and generating a real-time de-noised spectrogram, effectively reducing noise and enabling efficient signal detection and analysis over 30 GHz bandwidths with lower size, weight, and power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-rate ADCs are used to capture ultra-wide bandwidth signals, then measurement precision is improved, but device complexity and cost increase significantly
Solution Approach 1:
The ultra-wide bandwidth signal processing is segmented into multiple narrowband channels, each processed by a low-rate ADC. The received wideband signal is divided into frequency sub-bands using filter banks, with each sub-band processed independently by separate ADCs operating at reduced sampling rates, thereby capturing the full ultra-wide bandwidth without requiring a single high-rate ADC
Solution Approach 2:
The system transitions from time-domain sampling (single high-rate ADC) to frequency-domain processing (multiple low-rate ADCs with filter banks). By transforming the problem from temporal to spectral dimension, the system achieves equivalent measurement precision while using multiple lower-rate converters that are less complex and more cost-effective
2Measurement precision
If high power transmitters are used to detect targets at long range, then measurement precision is improved, but power consumption increases substantially
Solution Approach 1:
Multiple low-power transmitter channels are merged to achieve the equivalent performance of a single high-power transmitter. The system uses multiple transmit antennas with individual low-power amplifiers, combining their outputs through constructive interference to achieve long-range detection capability without requiring any single amplifier to operate at high power levels
Solution Approach 2:
Instead of using one high-power transmitter, the system creates multiple copies of low-power transmitter channels. Each copy operates independently at reduced power levels, and their combined effect through array processing and beamforming achieves the same detection precision as a single high-power transmitter would provide
3Use of energy by moving object
If larger antenna aperture is used to reduce transmit power, then power consumption is reduced, but weight increases making the approach infeasible
Solution Approach 1:
The system uses electronically controllable phased array technology where the beam direction and focus are dynamically adjusted through phase shifting of signals across multiple fixed, lightweight antenna elements. This dynamic beam steering capability replaces the need for large, heavy mechanical aperture structures, achieving long-range detection with reduced weight while maintaining low power consumption per element
4Measurement precision
If fast Fourier transform algorithms are used for signal processing, then measurement precision is improved, but computational complexity increases making real-time operation difficult
Solution Approach 1:
The complex wideband signal processing is segmented into multiple independent narrowband processing chains. Each channel processes a specific frequency sub-band using simplified algorithms, avoiding the need for computationally intensive full-bandwidth FFT operations. The results from all segments are then combined to achieve comprehensive signal analysis with reduced computational burden
Solution Approach 2:
Instead of performing complete FFT processing on the entire ultra-wide bandwidth signal, the system performs partial processing on segmented sub-bands. Each narrowband channel processes only its designated frequency portion with lower computational requirements, and the collective partial results provide sufficient measurement precision without the excessive computational complexity of full-spectrum processing
Data Source
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AI summary
A radar system including a transmit antenna for transmitting a radio frequency (RF) signal or a radar signal and a receive antenna for receiving a plurality of reflected signals created by a plurality of targets reflecting the RF signal or radar signal. The reflected signals include noise. The radar system also includes an analog-to-digital converter (ADC) that digitizes or samples the reflected signals to provide a digitized or sampled noisy input signal. The radar system further includes a reservoir computer that receives the noisy input signal. The reservoir computer includes a time-varying reservoir and is configured to de-noise the noisy input signal and provide a range measurement for each of the plurality of targets.