Design of Inertial Measurement Unit in Attitude and Heading Reference System for Real-Time Maneuver Monitoring by Using Kalman Filter

Masrafee, Md Masiat Roushan; Fardin, Nabia; Ahmed, Ashfaque; Hossam-E-Haider, Md

doi:10.1109/iceeict53905.2021.9667931

Cited by 2 publications

(1 citation statement)

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“…Whereas [27]- [32] provide a source of comparison with regards to spur suppression algorithmic complexity and achieved cancellation in full-duplex radios, [23]- [25], [33] in Table II present IMU-enabled motion compensation schemes, which yield an apt point of reference for the degree of fusion-enabled suppression achievable given both the compensation/processing time scale and computational complexity. While some of these prior works do indeed achieve noise/sideband suppression comparable to that of the designed IC, all entail either or both significant processing time intervals and/or unrealistic degrees of computational complexity, both of which ultimately preclude real-time, edgebased operation.…”

Section: Related Workmentioning

confidence: 99%

A 130-nm Fusion-Based Deconvolution Kernel Generator IC for Real-Time mmWave Radar Motion Compensation

Poole,

Arbabian

2023

IEEE Access

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High-resolution mmWave radar represents an attractive sensing modality for precise, real-time sensing on resource-limited edge devices. Inherent parasitic platform motion such as vibration, however, significantly degrades perception resolution. Although existing methods of motion compensation have addressed this issue, such algorithms entail compute-heavy post-processing and thus would not be feasible for short-time-scale operation on a resource-constrained edge device. We present the first known IC-enabled solution for vibratory motion compensation, in the form of a mixed-signal, real-time deconvolution kernel generator chip. The custom IC, implemented in the open-source SkyWater 130-nm technology, functions as a sensor-fusion-based filter generation engine, operating in processing windows of less than 95 ms and fusing synchronized data from an auxiliary accelerometer to synthesize a kernel capable of correcting the received radar signals in real time. Measurement results demonstrate accurate kernel generation, while yielding an average spur suppression of 35 dB across a range of vibration frequencies and amplitudes and 26 dB across measured target velocity. Such performance, in conjunction with the demonstrated operation on short time windows of radar data, validate the chip's potential for realistic deployment in real-time applications requiring high-resolution perception.

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