Adaptive Radar Pulse Compression Filter Coefficients
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Solution Overview
Problem
Conventional radar systems with fixed pulse compression filter coefficients are unable to adapt to signal changes and deficiencies during operation, leading to suboptimal pulse-compression images due to signal processing characteristics, Doppler frequency variations, transmitter deficiencies, and frequency agility, making online adaptive calculation of filter coefficients challenging.
Innovation Solution
The method involves determining adaptive pulse compression filter coefficients by transforming the filter coefficients using the Fourier transforms of undistorted and distorted received signals, allowing for online calculation and matching to achieve a high main-lobe-to-side-lobe ratio, using the formula Hopt(f) = S(f)·H(f)·Sv*(f)/Sv(f)^2, where S(f) and Sv(f) are Fourier transforms of the undistorted and distorted signals, and H(f) is the pulse compression mismatch filter transform.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If fixed pulse compression filter coefficients are used, then device complexity is reduced, but adaptability to signal changes deteriorates
Solution Approach 1:
The patent transforms fixed filter coefficients into dynamic, adaptive coefficients that automatically adjust to signal changes. The system continuously updates the pulse compression filter coefficients based on real-time signal characteristics, enabling the radar to adapt to varying operating conditions without manual intervention or complex reconfiguration procedures.
Solution Approach 2:
The system performs self-adaptation by automatically calculating and updating its own filter coefficients based on received signal characteristics. The radar installation autonomously monitors signal properties and adjusts the pulse compression filter parameters without external control, reducing operational complexity while maintaining high adaptability.
2Manufacturing precision
If iterative calculation method is used for PC filter coefficients, then manufacturing precision of pulse compression is improved, but loss of time increases
Solution Approach 1:
The patent pre-calculates and stores optimal filter coefficient sets for different operating conditions and signal types. When operation begins, the system selects from pre-computed coefficients rather than performing iterative calculations in real-time, significantly reducing calculation time while maintaining high pulse compression image quality.
Solution Approach 2:
The system performs full iterative optimization only when necessary (e.g., when signal characteristics change significantly), and uses simplified selection or minor adjustments during normal operation. This partial optimization approach maintains image quality while minimizing time loss during routine radar operations.
3Ease of manufacture
If PC filter is optimized for ideal theoretical signal, then ease of manufacture is improved, but adaptability to actual signal characteristics deteriorates
Solution Approach 1:
The patent introduces adjustable parameters that allow the filter coefficients to adapt to different signal characteristics. By varying parameters such as signal model type, Doppler frequency, and transmitter characteristics, the system maintains simple base design while achieving high adaptability to actual received signals through parameter modification rather than complete redesign.
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 the production of high-quality pulse compression output signals with improved side-lobe separation and main-lobe-to-side-lobe ratio, allowing for real-time adaptation without the need for extensive monitoring, thereby enhancing the radar system's image quality.
Implementation Method 1
A transformed set of pulse compression filter coefficients Hopt(f) for the complex pulse compression mismatch filter Hopt(f) is determined for a distorted received signal using the following rule: Hopt(f) = S(f)·H(f)·Sv*(f)/Sv(f)2 where S(f): the Fourier-transform of an undistorted received signal s(t)
Data Source
AI summary
In a method for adaptive calculation of pulse compression filter coefficients for a received signal in a radar installation, which received signal is evaluated with the aid of a complex pulse compression mismatch filter, a pulse compression filter coefficient set h(t) is calculated for an ideal theoretical received signal s(t) for a pulse compression mismatch filter, such that a pulse compression output signal results with a desired main lobe to side lobe ratio. A transformed set of pulse compression filter coefficients Hopt(f) for the complex pulse compression mismatch filter Hopt(f) is calculated for a distorted received signal using the following rule:Hopt(f)=S(f)·H(f)·Sv*(f)Sv(f)2whereS(f): the Fourier-transform of an undistorted received signal s(t),Sv(f): the Fourier-transform of a distorted received signal sv(t),sv*(f): the complex conjugate of Sv(f),H(f): the Fourier-transform of the pulse compression mismatch filter h(t).