Multi-Nyquist Signal Detection for DME Alias Separation
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Solution Overview
Problem
Distance Measuring Equipment (DME) systems face challenges in simultaneously sampling multiple frequency channels due to limitations in analog to digital converters, leading to interference from aliased signals, which existing methods struggle to effectively separate.
Innovation Solution
A system that includes an analog to digital converter, a clock signal generator, and a processor to iteratively sample and process signals across multiple Nyquist bands, selectively changing sampling rates to identify and eliminate interfering signals, allowing for efficient detection of DME signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a conventional single channel receiver using analog mixing and filtering is used, then the system can process signals within a limited frequency range, but it cannot simultaneously sample multiple frequency channels spread out over a larger frequency range
Solution Approach 1:
The patent segments the frequency range into multiple Nyquist bands, each sampled at different rates. The processor divides the broad frequency range into distinct segments (Nyquist bands) that can be independently sampled and processed, allowing coverage of a larger frequency range without requiring a single complex receiver for the entire range.
Solution Approach 2:
The patent employs dynamic sampling rates that can be adjusted for different Nyquist bands. The system dynamically changes sampling rates based on the specific frequency range being analyzed, allowing flexible adaptation to multiple frequency channels while using a single ADC structure.
2Adaptability or versatility
If analog techniques are used to select only a subset of DME channels prior to analog to digital conversion, then the ADC dynamic range requirements are reduced, but the system cannot detect signals across multiple Nyquist bands simultaneously
Solution Approach 1:
The patent performs preliminary spectral analysis to identify which Nyquist bands contain desired signals before full ADC conversion. By pre-processing the signal to determine signal locations across different bands, the system can then focus ADC resources on relevant frequency ranges, maintaining detection accuracy while expanding multi-band capability.
Solution Approach 2:
The system uses feedback from spectral pattern analysis to guide subsequent sampling and processing decisions. The processor analyzes spectral patterns to identify signal presence in different Nyquist bands and adjusts sampling strategies accordingly, ensuring accurate signal detection across multiple bands.
3Reliability
If signals are sampled at a fixed sampling rate, then the system structure is simple, but aliased signals from out-of-band frequencies cannot be effectively separated from non-aliased signals
Solution Approach 1:
The patent changes the sampling rate parameter dynamically to separate aliased from non-aliased signals. By varying the sampling rate and observing how spectral patterns change, the system can identify which signals are aliased (their spectral patterns change with sampling rate) and which are not, enabling reliable separation.
Solution Approach 2:
The system employs periodic sampling at different rates to distinguish aliased from non-aliased signals. By repeatedly sampling at varying rates and comparing spectral patterns, the system periodically identifies and separates aliased signals from genuine signals, improving reliability of signal detection.
Data Source
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AI summary
Systems and methods for detecting a signal across multiple Nyquist bands. The systems include an analog to digital converter (ADC), a clock signal generator configured to output a sample clock signal to the ADC, and a processor configured to process sampled signals and control the clock signal generator. The processor is configured to iteratively identify a desired signal, determine whether a possible interfering signal exists at a next sampling rate, and instruct the clock signal generator to generate the next sampling rate if the processor determines that a possible interfering signal does not exist. The methods include sampling an input signal at a first sampling rate, processing the sampled signal to extract information from a desired signal, determining whether a possible interfering signal exists at a next sampling rate, and sampling at the next sampling rate if it is determined that a possible interfering signal does not exist.