Fixed-Point First-Order Complementary Telemetry Filter (Q16.16)

Module 117 from the Davis Logic V2 project provides a real-time, first-order complementary telemetry filter for sensor fusion in embedded systems. The algorithm, authored by Jamie Davis and licensed under CC BY 4.0, merges high-frequency inertial data with low-frequency reference signals to produce a stabilized tracking vector. It is designed for zero-heap, zero-copy execution on low-power microcontrollers, with a file size of 63 bytes.

Use Cases

• Implementing low-latency orientation tracking for drones or robots based on the described complementary filter architecture.
• Benchmarking memory-efficient sensor fusion algorithms against Kalman filters for embedded projects.
• Studying integer-based, fixed-point (Q16.16) filter implementations to avoid floating-point overhead on microcontrollers.
• Developing noise-reduction and bias-drift suppression techniques for IMU data streams as described in the mathematical overview.

Strengths

• Designed for zero dynamic memory allocation (0 bytes heap), bounded within static registers.
• Employs 32-bit hardware-level saturation boundaries to prevent integer wrap-around errors.
• Algorithm is engineered to eliminate nested loops and matrix transposition, lowering dynamic current draw on microcontrollers.

Limitations

• Description metadata is limited; actual data quality and implementation details require manual inspection after download.
• Row count and column-level documentation are absent; field semantics must be inferred.
• The dataset is extremely small (63 bytes), indicating it is likely source code or documentation, not a traditional data corpus.

Provenance

Source

Jamie Davis (Independent Systems Architect), published on figshare.

Collection Method

Likely authored as a software module for the Davis Logic V2 architectural project.

Time Range

null

Freshness

Last updated 2026-05-31 20:58:12; freshness should be verified.

Geography

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