Special Issue "Radar Sensor for Motion Sensing and Automobile"

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Microwave and Wireless Communications".

Deadline for manuscript submissions: 30 September 2019.

Special Issue Editor

Guest Editor
Dr. Donghyun Baek

Microwave Embedded Circuit & System (MECAS) Lab., School of Electrical Engineering, Chung-Ang University, 84 Heukseok-ro, Dongjack-gu, Seoul 06974, Korea
Website | E-Mail
Interests: analog, RF, millimeter-wave, mixed-mode circuit and system design for mobile communications, radar sensors, and bio sensors

Special Issue Information

Dear Colleagues,

Recently, radar systems have received considerable attention in the consumer and industrial electronics, and automotive transportation, industries. The radar sensor detects the location and movement of nearby objects, providing assistance to the appliance user and increasing driving safety by decelerating in urgent situations or triggering safety equipment. Since radar is robust against environmental influences such as temperature, weather, and light conditions at an affordable cost, radars have rapidly expanding applications. This has been enabled by the recent development of device and circuit technologies, array antenna, and radar signal processing techniques. The objective of this Special Issue is to provide the latest research related to radar design for motion sensing and automobiles. The topics span from radar architecture, circuit technology, array antenna design, and radar signal processing, to practical applications and prototypes. This Special Issue of Electronics invites submissions of technical papers that may address, but are not limited to, the following: 

  • Radar Architecture: Doppler, FMCW, PMCW, FCW, UWB, etc.
  • Circuit Technology: Low-Noise Receiver, High-Efficiency Transmitter (Beamformer), Multichannel Transceiver, Signal Generator (VCO, PLL, Chirp Generator), etc.
  • Array Antenna Design: Array Design, Antenna Calibration, etc.
  • Radar Signal Processing: Beamforming, CFAR, Automatic Target Tracking, etc.
  • Radar Module and Applications

Dr. Donghyun Baek
Guest Editor

Manuscript Submission Information

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Keywords

  • radar sensor
  • Doppler radar
  • FMCW radar
  • UWB radar
  • motion sensor
  • automobile radar
  • radar transceiver
  • Radar on a Chip (ROC)

Published Papers (7 papers)

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Open AccessArticle
Multisensor RFS Filters for Unknown and Changing Detection Probability
Electronics 2019, 8(7), 741; https://doi.org/10.3390/electronics8070741
Received: 16 May 2019 / Revised: 19 June 2019 / Accepted: 28 June 2019 / Published: 30 June 2019
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Abstract
The detection probability is an important parameter in multisensor multitarget tracking. The existing multisensor multi-Bernoulli (MS-MeMBer) filter and multisensor cardinalized probability hypothesis density (MS-CPHD) filter require that detection probability is a priori. However, in reality, the value of the detection probability is constantly [...] Read more.
The detection probability is an important parameter in multisensor multitarget tracking. The existing multisensor multi-Bernoulli (MS-MeMBer) filter and multisensor cardinalized probability hypothesis density (MS-CPHD) filter require that detection probability is a priori. However, in reality, the value of the detection probability is constantly changing due to the influence of sensors, targets, and other environmental characteristics. Therefore, to alleviate the performance deterioration caused by the mismatch of the detection probability, this paper applies the inverse gamma Gaussian mixture (IGGM) distribution to both the MS-MeMBer filter and the MS-CPHD filter. Specifically, the feature used for detection is assumed to obey the inverse gamma distribution and is statistically independent of the target’s spatial position. The feature is then integrated into the target state to iteratively estimate the target detection probability as well as the motion state. The experimental results demonstrate that the proposed methods can achieve a better filtering performance in scenarios with unknown and changing detection probability. It is also shown that the distribution of the sensors has a vital influence on the filtering accuracy, and the filters perform better when sensors are dispersed in the monitoring area. Full article
(This article belongs to the Special Issue Radar Sensor for Motion Sensing and Automobile)
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Open AccessArticle
915-MHz Continuous-Wave Doppler Radar Sensor for Detection of Vital Signs
Electronics 2019, 8(5), 561; https://doi.org/10.3390/electronics8050561
Received: 26 April 2019 / Revised: 15 May 2019 / Accepted: 17 May 2019 / Published: 20 May 2019
Cited by 2 | PDF Full-text (6534 KB) | HTML Full-text | XML Full-text | Correction
Abstract
A miniaturized continuous-wave Doppler radar sensor operating at 915 MHz to remotely detect both respiration and heart rate (beats per minute) is presented. The proposed radar sensor comprises a front-end module including an implemented complementary metal-oxide semiconductor low-noise amplifier (LNA) and fractal-slot patch [...] Read more.
A miniaturized continuous-wave Doppler radar sensor operating at 915 MHz to remotely detect both respiration and heart rate (beats per minute) is presented. The proposed radar sensor comprises a front-end module including an implemented complementary metal-oxide semiconductor low-noise amplifier (LNA) and fractal-slot patch antennas, whose area was reduced by 15.2%. The two-stage inverter-based LNA was designed with an interstage capacitor and a feedback resistor to acquire ultrawide bandwidth. Two operating frequencies, 915 MHz and 2.45 GHz, were analyzed with regard to path loss for efficient operation because frequency affects detection sensitivity, reflected signal power from the human body, and measurement distance in a far-field condition. Path-loss calculation based on the simplified layer model indicates that the reflected power of the 915 MHz radar could be higher than that of the 2.45 GHz radar. The implemented radar front-end module excluding the LNA occupies 35 × 55 mm2. Vital signs were obtained via a fast Fourier transform and digital filtering using raw signals. In an experiment with six subjects, the respiration and heart rate obtained at 0.8 m using the proposed radar sensor exhibited mean accuracies of 99.4% and 97.6% with respect to commercialized reference sensors, respectively. Full article
(This article belongs to the Special Issue Radar Sensor for Motion Sensing and Automobile)
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Open AccessArticle
A Novel Multi-Input Bidirectional LSTM and HMM Based Approach for Target Recognition from Multi-Domain Radar Range Profiles
Electronics 2019, 8(5), 535; https://doi.org/10.3390/electronics8050535
Received: 4 April 2019 / Revised: 4 May 2019 / Accepted: 8 May 2019 / Published: 13 May 2019
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Abstract
Radars, as active detection sensors, are known to play an important role in various intelligent devices. Target recognition based on high-resolution range profile (HRRP) is an important approach for radars to monitor interesting targets. Traditional recognition algorithms usually rely on a single feature, [...] Read more.
Radars, as active detection sensors, are known to play an important role in various intelligent devices. Target recognition based on high-resolution range profile (HRRP) is an important approach for radars to monitor interesting targets. Traditional recognition algorithms usually rely on a single feature, which makes it difficult to maintain the recognition performance. In this paper, 2-D sequence features from HRRP are extracted in various data domains such as time-frequency domain, time domain, and frequency domain. A novel target identification method is then proposed, by combining bidirectional Long Short-Term Memory (BLSTM) and a Hidden Markov Model (HMM), to learn these multi-domain sequence features. Specifically, we first extract multi-domain HRRP sequences. Next, a new multi-input BLSTM is proposed to learn these multi-domain HRRP sequences, which are then fed to a standard HMM classifier to learn multi-aspect features. Finally, the trained HMM is used to implement the recognition task. Extensive experiments are carried out on the publicly accessible, benchmark MSTAR database. Our proposed algorithm is shown to achieve an identification accuracy of over 91% with a lower false alarm rate and higher identification confidence, compared to several state-of-the-art techniques. Full article
(This article belongs to the Special Issue Radar Sensor for Motion Sensing and Automobile)
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Open AccessArticle
Multi-Sensor Optimization Scheduling for Target Tracking Based on PCRLB and a Novel Intercept Probability Factor
Electronics 2019, 8(2), 140; https://doi.org/10.3390/electronics8020140
Received: 21 January 2019 / Accepted: 26 January 2019 / Published: 29 January 2019
Cited by 1 | PDF Full-text (6078 KB) | HTML Full-text | XML Full-text
Abstract
In order to improve the survivability of active sensors, the problem of low probability of intercept (LPI) for a multi-sensor network system is studied in this paper. Two kinds of operational requirements are taken into account, the first of which is to ensure [...] Read more.
In order to improve the survivability of active sensors, the problem of low probability of intercept (LPI) for a multi-sensor network system is studied in this paper. Two kinds of operational requirements are taken into account, the first of which is to ensure the survivability of sensors and the second is to improve the tracking accuracy of targets as much as possible. Firstly, the sensor tracking model and the posterior Carmér-Rao lower bound (PCRLB) of the target are presented to evaluate the sensor tracking benefits in next time. Then, a novel intercept probability factor (IPF) is proposed for multi-sensor multi-target tracking scenarios. At the basis of PCRLB and IPF, a myopic multi-sensor scheduling model for target tracking is set up to control the intercepted probability of sensors and improve the target tracking accuracy. At last, a fast solution algorithm based on an improved particle swarm optimization (PSO) algorithm is given to obtain the optimal scheduling actions. Simulation of experimental results show that the proposed model can effectively control the intercepted risk of every sensor, which can also obtain better target tracking performance than existing multi-sensor scheduling methods. Full article
(This article belongs to the Special Issue Radar Sensor for Motion Sensing and Automobile)
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Open AccessArticle
A Multi-Mode Sensor Management Approach in the Missions of Target Detecting and Tracking
Electronics 2019, 8(1), 71; https://doi.org/10.3390/electronics8010071
Received: 11 December 2018 / Revised: 26 December 2018 / Accepted: 4 January 2019 / Published: 8 January 2019
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Abstract
In this paper, sensor management is divided into two processes: sensor deployment and sensor scheduling, after which a multi-mode sensor management approach based on risk theory is proposed. Firstly, the definition of risk is provided, on the basis of which the target detecting [...] Read more.
In this paper, sensor management is divided into two processes: sensor deployment and sensor scheduling, after which a multi-mode sensor management approach based on risk theory is proposed. Firstly, the definition of risk is provided, on the basis of which the target detecting risk and the target tracking risk are separately presented, along with their computing methods. Secondly, when deploying sensors, the objective is to obtain the minimum target detecting risk. Similarly, when scheduling sensors, the objective is to obtain the minimal sum of target detecting risk and target tracking risk. Furthermore, to obtain sensor management schemes according to the objective functions, the improved bee colony algorithm based on double-probability and in combination with the particle swarm optimization algorithm is proposed. Finally, simulations are conducted, which indicate that the models and the algorithm in the paper possess some advantages over existing ones. Full article
(This article belongs to the Special Issue Radar Sensor for Motion Sensing and Automobile)
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Open AccessCorrection
Correction: Park, J.-H. et al. 915-MHz Continuous-Wave Doppler Radar Sensor for Detection of Vital Signs. Electronics 2019, 8, 561
Electronics 2019, 8(8), 855; https://doi.org/10.3390/electronics8080855
Received: 22 July 2019 / Accepted: 29 July 2019 / Published: 31 July 2019
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Abstract
The authors wish to make the following corrections to the published paper [...] Full article
(This article belongs to the Special Issue Radar Sensor for Motion Sensing and Automobile)
Open AccessLetter
Elimination of Motion-Induced Phase Based on Double-Time Switching Scheme for SAA FMCW Radar
Electronics 2019, 8(7), 786; https://doi.org/10.3390/electronics8070786
Received: 1 June 2019 / Revised: 4 July 2019 / Accepted: 12 July 2019 / Published: 14 July 2019
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Abstract
Due to the low cost and straightforward structure, the switch antenna array (SAA) frequency modulated continuous wave (FMCW) radar has been widely applied in many fields. However, the motion-induced phase always leads to inaccurate direction estimation of moving targets. Here, we proposed an [...] Read more.
Due to the low cost and straightforward structure, the switch antenna array (SAA) frequency modulated continuous wave (FMCW) radar has been widely applied in many fields. However, the motion-induced phase always leads to inaccurate direction estimation of moving targets. Here, we proposed an elimination method of the motion-induced phase for the SAA FMCW radar. A double-time switching scheme (DTSS) is used for the reception of echo signals. Elimination of motion-induced phase is completed without estimating velocity, which can avoid the ambiguous velocity estimation problem. Additionally, the direction estimation of the moving target can be obtained by directly using a conventional digital beam forming (DBF) algorithm. The validity of the proposed method has been proved by the simulated and experimental results. Full article
(This article belongs to the Special Issue Radar Sensor for Motion Sensing and Automobile)
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