Adaptive Filter Tap Selection for Narrowband Jammer Suppression
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Solution Overview
Problem
Modern communication systems face challenges in reducing signal interference due to both unintentional and intentional narrowband jammers, particularly in wideband radio channels, where existing adaptive filters often require complex designs and may not effectively handle multiple interferers while meeting hardware constraints such as size, weight, and power limitations.
Innovation Solution
The system employs an adaptive filter with a variable delay circuit and tap order selection mechanism, using Least Mean Squares (LMS), Recursive Least Squares (RLS), or Minimum Mean-Square Error (MMSE) estimation algorithms to adjust coefficients and select the optimal number of taps based on output power and modulation type, allowing for improved multipath performance and interference suppression.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If adaptive filters with more filter taps are used to handle multiple interferers, then interference suppression capability is improved, but device complexity and hardware resource consumption increase
Solution Approach 1:
The patent implements dynamic adaptation of filter parameters including variable tap spacing and adjustable tap order based on detected interferer characteristics. The filter transitions from static design to dynamic reconfiguration, allowing optimal performance with fewer taps by adapting to specific interference scenarios rather than being over-designed for worst-case situations
Solution Approach 2:
The system changes filter parameters such as tap spacing, tap order, and adaptation algorithms based on detected interferer types and conditions. This allows the same physical filter hardware to achieve different suppression capabilities by reconfiguring parameters, effectively handling multiple interferers without increasing physical complexity
2Adaptability or versatility
If faster adaptation speed is implemented to track changing interferers, then adaptability is improved, but use of energy and computational resources increase
Solution Approach 1:
The adaptation speed is made dynamic rather than fixed - the system adjusts the rate of coefficient updates based on interferer stability and detection confidence. When interferers are stable, adaptation slows to conserve energy; when interferers change rapidly, adaptation accelerates to maintain suppression effectiveness
Solution Approach 2:
The filter uses periodic detection and evaluation of interferer characteristics to determine when full adaptation is necessary versus when lighter processing suffices. This periodic assessment allows the system to cycle between high and low power states rather than maintaining constant high-performance adaptation
3Reliability
If more filter taps are used to improve interference suppression, then narrowband interferer handling is improved, but platform constraints such as FPGA usage and size are exceeded
Solution Approach 1:
Instead of using a large fixed number of taps, the system dynamically selects and adjusts the number of active taps based on interferer characteristics. This allows achieving equivalent or superior suppression with fewer physical taps by concentrating filtering resources on the most relevant frequency components
Solution Approach 2:
The system changes the effective filter order and tap configuration based on detected interferer types. Rather than always using maximum taps, it adapts the tap structure to match the interference profile, reducing FPGA resource consumption while maintaining suppression effectiveness
4Reliability
If adaptive filtering is applied to the data portion of waveform, then interference reduction is improved, but distortion of the intended message content may occur
Solution Approach 1:
The patent segments the waveform into distinct portions (preamble and data) and applies different filtering strategies to each. The preamble receives aggressive adaptive filtering for interferer characterization, while the data portion uses more conservative filtering with parameters optimized to preserve signal integrity while maintaining suppression
Data Source
AI summary
A communications system receives a modulated signal that carries encoded communications data. An adaptive filter has an input, a plurality of non-adaptive and adaptive filter taps with weighted coefficients, and an output. The received signal is passed through the adaptive filter and around adaptive filter and a switch selects which signal to pass to demodulator based on measured output power of the adaptive filter and of the original received signal. A demodulator and decoder receive the filtered output signal and demodulate and decode the signal to obtain the communications data.