Improved FMCW Radar System for Multi-Target Detection of Human Respiration Vital Sign

Pratiwi, Hana; Hidayat, Mujib R.; Pramudita, Aloysius Adya; Suratman, Fiky Yosef

doi:10.14203/jet.v19.38-44

Cited by 11 publications

(5 citation statements)

References 14 publications

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“…To estimate the number of targets with the APES approach on the MIMO radar is stated by [7], as written in (4).…”

Section: B Apes Methods On the Mimo Radarmentioning

confidence: 99%

“…The determination of the waveform plays a major role in the resolution of some of these parameters, such as in research [3] where the non-linear frequency modulation type signal is used on the radar. To achieve the detection of multiple targets, a frequency modulation continuous wave (FMCW) signal can be used as reported in research [4]. Likewise, with the development of the automotive radar, it is necessary to have a radar that has a reliable and high-resolution angle of detection [5].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

DOA Signal Identification Based on Amplitude and Phase Estimation for Subarray MIMO Radar Applications

Mahdi

Tahcfulloh

2022

J. Elektron. dan Telekomun.

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The overlapped equal subarray transmit radar, which is also known as the Subarray Multiple-Input Multiple-Output radar, utilizes the key advantages simultaneously of both types of multi-antenna radar, i.e. the phased array and MIMO radars, so that it is able to detect multiple targets even though it has a radar cross section (RCS) of a weak or small target. In this paper, it is proposed to develop a parameter estimation approach called amplitude and phase estimation (APES). This approach provides improved resolution to the estimation of the amplitude and direction of arrival (DoA) of the target reflection signal on the radar compared to the existing conventional estimation methods such as least squares (LS). The formulation of the APES method on this radar is based on the tested parameters such as DoA and RCS and continuously being evaluated. The results show that the performance of the APES method of this radar can detect targets very precisely when the number of subarrays (M) is greater than the number of detection targets (P), precisely M > P. For the results of DoA and RCS accuracy from the APES method, this radar is more accurate than the LS when testing the angular resolution between the two targets, an angle resolution of 2° is obtained for the APES method which is superior to the LS with an angle resolution of 5.8°. In these conditions, the APES method is able to accurately distinguish between two targets while the LS method is only able to detect one target.

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“…To estimate the number of targets with the APES approach on the MIMO radar is stated by [7], as written in (4).…”

Section: B Apes Methods On the Mimo Radarmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

DOA Signal Identification Based on Amplitude and Phase Estimation for Subarray MIMO Radar Applications

Mahdi

Tahcfulloh

2022

J. Elektron. dan Telekomun.

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“…Two double-balanced mixers are combined. By changing the Inphase (I) and quadrature (Q) inputs in the branches of the IQ demodulator (1), the LPF output is combined with a reference signal [4]. Reference signals are written as (2) [4].…”

Section: A Fmcw Radar Module and Block Diagrammentioning

confidence: 99%

“…By changing the Inphase (I) and quadrature (Q) inputs in the branches of the IQ demodulator (1), the LPF output is combined with a reference signal [4]. Reference signals are written as (2) [4]. The phase data can then be obtained using the arctangent computation.…”

Section: A Fmcw Radar Module and Block Diagrammentioning

confidence: 99%

Analyze Transmission Data from a Multi-Node Patient's Respiratory FMCW Radar to the Internet of Things

Rahmatullah¹,

Adi²,

Prasetya³

et al. 2023

IJACSA

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This is the development of a system that has been made, FMCW radar for human or patient breathing which will then determine the type of disease or disorder in the patient just by looking at the type of breathing. This research uses data from FMCW Radar for human or patient breathing, which is then converted to data that can be read in real-time by the public, doctors, or medical teams through a web server; the web server used is iotmedis.brin.go.id. The novelty of this study is that various types of respiratory data are taken from various points so that it will cause new analysis, namely the process of transmitting data on server traffic or uplink and downlink processes. Specific data and research novelty is how Multi patient respiratory data from OmnipreSense or FMCW Radar can be processed by a microprocessor using MQTT, and multi-patient data can be displayed on the server in real-time.

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“…Like a vehicular radar, a radar with high accuracy and resolution for the detection of multiple targets is absolutely necessary [1], [2]. As a radar for detecting vital human organs, a radar that detects multiple targets with slow motion is needed [3] as well as for other applications.…”

Section: Introductionmentioning

confidence: 99%

Parameter Estimation and Target Detection of Phased-MIMO Radar Using Capon Estimator

Tahcfulloh

Hardiwansyah

2020

indones.j.electron.telecommun.

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Phased-Multiple Input Multiple Output (PMIMO) radar is multi-antenna radar that combines the main advantages of the phased array (PA) and the MIMO radars. The advantage of the PA radar is that it has a high directional coherent gain making it suitable for detecting distant and small radar cross-section (RCS) targets. Meanwhile, the main advantage of the MIMO radar is its high waveform diversity gain which makes it suitable for detecting multiple targets. The combination of these advantages is manifested by the use of overlapping subarrays in the transmit (Tx) array to improve the performance of parameters such as angle resolution and detection accuracy at amplitude and phase proportional to the maximum number of detectable targets. This paper derives a parameter estimation formula with Capon's adaptive estimator and evaluates it for the performance of these parameters. Likewise, derivation for expressions of detection performance such as the probability of false alarm and the probability of detection is also given. The effectiveness and validation of its performance are compared to conventional estimator for other types of radars in terms of the effect of the number of target angles, the RCS of targets, and variations in the number of subarrays at Tx of this radar. Meanwhile, the detection performance is evaluated based on the effect of Signal to Noise Ratio (SNR) and the number of subarrays at Tx. The evaluation results of the estimator show that it is superior to the conventional estimator for estimating the parameters of this radar as well as the detection performance. Having no sidelobe makes this estimator strong against the influence of interference and jamming so that it is suitable and attractive for the design of radar systems. Root mean square error (RMSE) on magnitude detection from LS and Capon estimators were 0.033 and 0.062, respectively. Meanwhile, the detection performance for this radar has the probability of false alarm above 10-4 and the probability of detection of more than 99%.

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Improved FMCW Radar System for Multi-Target Detection of Human Respiration Vital Sign

Cited by 11 publications

References 14 publications

DOA Signal Identification Based on Amplitude and Phase Estimation for Subarray MIMO Radar Applications

DOA Signal Identification Based on Amplitude and Phase Estimation for Subarray MIMO Radar Applications

Analyze Transmission Data from a Multi-Node Patient's Respiratory FMCW Radar to the Internet of Things

Parameter Estimation and Target Detection of Phased-MIMO Radar Using Capon Estimator

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