Non-linear FM Radar Signal Processing for Range Tracking
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Solution Overview
Problem
Current radar systems face challenges in accurately tracking targets using conventional linear FM signals, as they struggle to effectively estimate range and closing velocity, especially in dynamic scenarios where signals are subject to varying Doppler shifts and range changes.
Innovation Solution
The implementation of a radar system that emits non-linear swept electromagnetic FM signals, processed by an electronic waveform processor using modules such as Emitted Signal Characteristics, Quad Regression, Quad Derivation, Doppler Adjust, Linear Regression, Variance, and Refining modules to calculate and refine estimates of range and closing velocity, leveraging the characteristics of the signals' frequency changes and Doppler shifts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional linear FM signals are used for target tracking, then the radar system structure is simple, but the tracking accuracy deteriorates in dynamic scenarios with varying Doppler shifts and range changes
Solution Approach 1:
The patent transforms the conventional linear FM signal into a non-linear FM signal by changing the frequency modulation parameter from linear to quadratic. This parameter change enables the signal to better match the chirp rate variations caused by Doppler shifts and range changes, thereby improving tracking accuracy without requiring complex adaptive processing algorithms
Solution Approach 2:
The patent pre-compensates for Doppler effects by embedding quadratic phase terms in the transmitted signal before transmission. This preliminary action counteracts the expected Doppler shifts and range variations, allowing the receiver to use simpler processing to achieve high tracking accuracy in dynamic scenarios
2Measurement precision
If non-linear swept electromagnetic FM signals are used, then the estimation precision of range and closing velocity improves, but the device complexity increases due to multiple processing modules
Solution Approach 1:
The waveform processor is segmented into distinct functional modules (quadratic derivative module, quadratic regression module, Doppler adjust module, linear regression module, variance module, refining module). Each module performs a specific function in the signal processing chain, making the complex processing task manageable and allowing for optimized implementation of each function
Solution Approach 2:
The patent implements iterative refinement where the variance module calculates measurement uncertainty and the refining module uses this information to adjust estimates. This feedback mechanism allows the system to adaptively improve range and velocity estimates based on the quality of the signal and environmental conditions
3Adaptability or versatility
If non-linear FM signals with quadratic phase are transmitted, then the ability to track targets with changing velocity improves, but the signal processing difficulty increases due to Doppler shift variations
Solution Approach 1:
The patent changes the frequency modulation parameter from linear to quadratic, which fundamentally alters how the signal interacts with moving targets. The quadratic phase evolution matches the kinematic equations of uniformly accelerated motion, enabling direct extraction of target parameters without complex de-chirping or correlation operations that would be required with linear FM signals
Solution Approach 2:
The patent replaces complex mechanical tracking adjustments with signal processing substitutions. Instead of mechanically adjusting the radar beam to track accelerating targets, the system uses quadratic FM signals whose frequency evolution mathematically substitutes for the mechanical tracking motion, simplifying the overall system while improving performance
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 enables precise estimation and refinement of target range and closing velocity, improving tracking accuracy even in scenarios with changing conditions, by accurately processing the non-linear signal characteristics and adjusting for Doppler shifts and variance.
Implementation Method 1
an electronic transmitter adapted to emit a non-linear swept electromagnetic FM signal
Implementation Method 2
struggle to effectively estimate range and closing velocity, especially in dynamic scenarios where signals are subject to varying Doppler shifts and range changes
Data Source
AI summary
Systems include at least one electronic waveform processor operatively associated with at least one reflected signal electronic sensor and configured and programmed to generate an estimate of the range from an object to a target and an estimate of the closing velocity of the object to the target using a reflected signal. Systems use a non-linear swept electromagnetic FM signal.