Sigma-Delta Pressure Sensor for Low-Latency Rate Measurements
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Solution Overview
Problem
Current air data sensors face challenges in providing precise, low-noise, and low-latency pressure measurements due to signal aliasing and noise issues, which are exacerbated by discrete sampling and inadequate filtering, leading to reduced accuracy and increased latency in altitude and airspeed rate calculations.
Innovation Solution
An integrated sensor system that embeds a synchronous time stamp with each measurement, using a sigma-delta A/D converter and internal data acquisition to minimize noise and latency, allowing external processing to compute rate parameters with improved resolution and accuracy, and features electrostatic shielding and hermetic packaging for environmental protection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If prefiltering is applied to minimize aliasing and noise in discrete sampling systems, then measurement precision is improved, but latency increases and system responsiveness decreases
Solution Approach 1:
The patent replaces the mechanical/discrete sampling approach with a continuous sigma-delta modulation system. Instead of sampling at discrete intervals and applying prefiltering, the system uses continuous oversampling and digital filtering, eliminating the need for analog prefiltering and reducing latency while maintaining measurement precision.
Solution Approach 2:
The patent changes the sampling parameter by using oversampling at a rate much higher than the Nyquist frequency. This allows the system to achieve high measurement precision through digital averaging and filtering without requiring aggressive prefiltering, thereby reducing latency and improving system responsiveness.
2Measurement precision
If heavy filtering is applied to reduce noise in rate parameter measurements, then measurement precision is improved, but latency increases
Solution Approach 1:
The patent replaces heavy analog filtering with digital filtering performed on oversampled data. The sigma-delta modulation provides inherent noise shaping that pushes quantization noise to higher frequencies, allowing digital low-pass filtering to achieve low noise levels without requiring heavy filtering that would increase latency.
Solution Approach 2:
The patent uses periodic oversampling at a high frequency to achieve noise reduction through digital averaging. By sampling continuously at a rate much higher than the signal bandwidth and applying digital decimation filtering, the system achieves low noise in rate parameter measurements without the latency penalty of heavy analog filtering.
3Device complexity
If discrete sampling is used in interrupt-based timing loops, then device complexity is reduced, but measurement precision deteriorates due to aliasing and noise
Solution Approach 1:
The patent replaces the simple interrupt-based discrete sampling system with a sigma-delta modulation architecture. The sensor output is continuously modulated and oversampled, providing high-resolution data that is resistant to aliasing and noise. The increased measurement precision is achieved through the modulation scheme itself rather than through complex post-processing.
Solution Approach 2:
The patent implements continuous oversampling and modulation rather than discrete periodic sampling. The sigma-delta modulator continuously converts the analog sensor output to a high-frequency digital bit stream, providing continuous measurement information that is inherently resistant to aliasing and allows for flexible digital filtering without losing measurement precision.
4Device complexity
If jitter in time of data measurement occurs, then device complexity is reduced, but measurement precision deteriorates due to noise in rate calculations
Solution Approach 1:
The patent replaces time-based discrete sampling with event-driven sigma-delta modulation. Each measurement is time-stamped with high precision, and the oversampled nature of the data provides redundant information that compensates for any timing jitter. The continuous modulation ensures that rate calculations can be performed with high precision even if the external sampling timing is not perfectly regular.
Data Source
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AI summary
An integrated sensor implementation employs a data acquisition method for producing digital output signals that enables computing low latency, low noise, rate of pressure (or altitude etc.) change measurements. An example sensor includes a self-digitizing pressure and temperature sensor circuit that outputs a serial digital signal that varies with at least one physical parameter to which the sensor circuit is exposed. The sensor incorporates an internal sigma-delta A/D converter and digital data acquisition device that effectively time-stamps all acquired data. This time stamped data is then transmitted to an external processing resource (microprocessor) that is used to convert the self-digitized, time stamped data into low latency, low-noise proportional and rate parameter outputs having the desired engineering units for at least one physical parameter sensed. This low-latency, low noise rate of change signal may be derived without the latency penalty of digital filtering.