Indoor non‐rhythmic human motion classification using a frequency‐modulated continuous‐wave radar

Zou, Yu; Ding, Chuanwei; Hong, Hong; Li, Changzhi; Zhu, Xiaohua

doi:10.1049/joe.2019.0560

Cited by 2 publications

(2 citation statements)

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“…Moreover a range-Doppler map [19] can be generated by coupling range and micro-Doppler features. Zou et al [20] combined range and Doppler features based on radar signals to recognise human motions; however, they did not realize realtime recognition. This is a problem that needs to be solved.…”

Section: Related Workmentioning

confidence: 99%

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Real‐time recognition of human motions using multidimensional features in ultrawideband biological radar

2021

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Human motion recognition for biological radar has made astonishing progress. However, in some applications with high real-time requirements, it is difficult for existing approaches to achieve high accuracy. A multidimensional features long short-term memory (LSTM) neural network model is presented using multibranch network structure and high-dimensional radar feature fusion, which can recognise motions of human in real time, even in the presence of occlusions. The features selected for motion recognition including slow time range-map and slow time Doppler map. A single feature-based representation is not enough to capture the variations and attributes of individuals (range, velocity, etc.); thus, the fusion of multiple features is significant for recognising motions. Furthermore, because action reflects the behaviour of a human within a period, and the start and end are unavailable, intercepting fixed-length data in the time domain for recognition is not feasible. Thus, we introduce an approach based on an LSTM network that extracts features along the time dimension. Experiments show that the proposed approach is effective. A recognition accuracy of above 93.38% is achieved.This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

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Section: Related Workmentioning

confidence: 99%

“…Zou et al. [20] combined range and Doppler features based on radar signals to recognise human motions; however, they did not realize real‐time recognition. This is a problem that needs to be solved.…”

Section: Related Workmentioning

confidence: 99%