Radar Phase Processor Frequency Domain Motion Discrimination
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Solution Overview
Problem
Current radar systems are unable to effectively distinguish between objects with simple and complex dynamic motions, leading to difficulties in discriminating between targets and clutter, particularly in cases where objects exhibit random motion.
Innovation Solution
A radar system that processes phase changes in return signals by converting phase data to the frequency domain and analyzing pulse-to-pulse phase fluctuations to differentiate between simple and complex dynamic motions, using techniques such as phase unwrapping and high-frequency spectral analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional Doppler frequency filters and time domain analysis are used, then the system can detect target velocity and basic motion characteristics, but the system cannot discriminate between objects with simple dynamic motions and those having complex dynamic motions
Solution Approach 1:
The patent transforms the analysis from the time domain to the frequency domain by applying Fast Fourier Transform (FFT) to the phase data. This dimensional transformation enables the system to analyze phase fluctuations at different frequency components, revealing whether motion is simple (single frequency) or complex (multiple frequencies), thereby achieving motion discrimination that was not possible with traditional time domain analysis alone.
Solution Approach 2:
The system changes the analysis parameter from time-domain velocity measurements to frequency-domain phase fluctuation analysis. By examining the spectral content of phase variations rather than just velocity magnitude, the system can distinguish between simple periodic motions (single frequency peaks) and complex random motions (broad spectral distribution), enhancing measurement precision without requiring additional hardware.
2Measurement precision
If the system analyzes radar cross-section and kinematics for target discrimination, then it can identify targets based on velocity and acceleration, but it lacks the ability to distinguish between objects maintaining fixed attitude and those with random motion
Solution Approach 1:
The system performs preliminary phase unwrapping and filtering operations on the raw phase data before spectral analysis. By pre-processing the phase data to remove ambiguities and noise, the system prepares the signal for accurate frequency domain transformation, ensuring that the subsequent FFT analysis accurately reflects the true motion characteristics without losing critical attitude information.
Solution Approach 2:
The patent introduces phase data as an intermediary parameter between the raw radar return signal and the final target characterization. Instead of directly analyzing radar cross-section or velocity, the system extracts phase information as an intermediate representation that encodes attitude and orientation changes, then uses FFT to decode this intermediate representation into motion type classification.
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 allows for improved discrimination between stable and unstable targets, enhancing the system's ability to accurately identify and separate true targets from clutter, even when objects exhibit complex dynamic behaviors.
Implementation Method 1
A radar system is useful for detecting, characterizing and monitoring various kinematic parameters associated with natural and/or man-made objects... These systems typically transmit 'beams' or electromagnetic (EM) signals intended to engage one or more objects or targets, and process reflected return signals
Implementation Method 2
process reflected return signals (or echoes) for measuring spatial features, object identification and characterization
Implementation Method 3
A phase processor responsive to the output of the receiver and configured to extract phase data as a function of time from a received return signal... convert the extracted phase data to the frequency domain
Implementation Method 4
convert the extracted phase data to the frequency domain, and analyze the converted phase data to identify phase changes indicative of a type of motion
Implementation Method 5
Many of these employ clutter cancellation methods that rely on the principle that moving targets have a Doppler frequency shift, while stationary targets do not. Thus, pulse-Doppler radar systems may implement a plurality of Doppler frequency filters
Data Source
AI summary
A radar system includes a transmitter configured to generate a series of electromagnetic pulses, and a receiver configured to receive return signals reflected by an object of interest from the series of electromagnetic pulses. A phase processor is operatively connected to the output of the receiver and configured to extract phase data as a function of time from the received return signals, convert the extracted phase data to the frequency domain, and analyze the phase data to identify phase changes indicative of one or more types of motion, such as complex or simple dynamic motion of the object of interest.