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11 pages, 9328 KiB

Open AccessArticle

Tilted-Beam Switched Array Antenna for UAV Mounted Radar Applications with 360° Coverage

by Cheol Ung Lee, Gunhark Noh, ByungKuon Ahn, Jong-Won Yu and Han Lim Lee

Electronics 2019, 8(11), 1240; https://doi.org/10.3390/electronics8111240 - 30 Oct 2019

Cited by 17 | Viewed by 5348

Abstract

A highly efficient antenna array for unmanned aerial vehicle (UAV) mounted radar applications with a tilted-beam characteristic and a 360° beam coverage is proposed in this paper. The proposed array antenna is configured by four planar super J-pole antennas with 2-dimensional ground reflectors. [...] Read more.

A highly efficient antenna array for unmanned aerial vehicle (UAV) mounted radar applications with a tilted-beam characteristic and a 360° beam coverage is proposed in this paper. The proposed array antenna is configured by four planar super J-pole antennas with 2-dimensional ground reflectors. Each super J-pole antenna element provides a high directivity where the peak gain is tilted about 45° facing toward the ground from the bottom of a UAV body. Thus, the air-to-ground communication difficulty due to the altitude difference between the UAV and ground targets can be effectively solved. Further, the four super J-pole elements with a switched operation can cover the whole 360° areas around the UAV while high antenna gain is maintained. To verify the performance, the proposed structure was implemented at 5.9 GHz with an overall volume of 0.88 × 0.88 × 0.83 λ_o³. The measured 10-dB impedance bandwidths for all four antenna elements were better than 27.2% and the isolation among the four antenna ports was also always better than 13 dB. The measured peak gain was better than 7.4 dBi and tilted at 45° in the elevation angle. Lastly, the measured half power beam widths in elevation and azimuth planes were more than 60° and 87°, respectively. Full article

(This article belongs to the Special Issue Radar Sensor for Motion Sensing and Automobile)

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17 pages, 3758 KiB

Open AccessArticle

Multisensor RFS Filters for Unknown and Changing Detection Probability

by Zhiguo Zhang, Qing Li and Jinping Sun

Electronics 2019, 8(7), 741; https://doi.org/10.3390/electronics8070741 - 30 Jun 2019

Cited by 4 | Viewed by 2231

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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14 pages, 6534 KiB

Open AccessArticle

915-MHz Continuous-Wave Doppler Radar Sensor for Detection of Vital Signs

by Jae-Hyun Park, Yeo-Jin Jeong, Ga-Eun Lee, Jun-Taek Oh and Jong-Ryul Yang

Electronics 2019, 8(5), 561; https://doi.org/10.3390/electronics8050561 - 20 May 2019

Cited by 19 | Viewed by 7413 | 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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28 pages, 4971 KiB

Open AccessArticle

A Novel Multi-Input Bidirectional LSTM and HMM Based Approach for Target Recognition from Multi-Domain Radar Range Profiles

by Fei Gao, Teng Huang, Jun Wang, Jinping Sun, Amir Hussain and Huiyu Zhou

Electronics 2019, 8(5), 535; https://doi.org/10.3390/electronics8050535 - 13 May 2019

Cited by 12 | Viewed by 4318

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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22 pages, 6078 KiB

Open AccessArticle

Multi-Sensor Optimization Scheduling for Target Tracking Based on PCRLB and a Novel Intercept Probability Factor

by Gongguo Xu, Ce Pang, Xiusheng Duan and Ganlin Shan

Electronics 2019, 8(2), 140; https://doi.org/10.3390/electronics8020140 - 29 Jan 2019

Cited by 24 | Viewed by 3582

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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18 pages, 3221 KiB

Open AccessArticle

A Multi-Mode Sensor Management Approach in the Missions of Target Detecting and Tracking

by Ce Pang, Ganlin Shan, Xiusheng Duan and Gongguo Xu

Electronics 2019, 8(1), 71; https://doi.org/10.3390/electronics8010071 - 8 Jan 2019

Cited by 20 | Viewed by 2680

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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1 pages, 154 KiB

Open AccessCorrection

Correction: Park, J.-H. et al. 915-MHz Continuous-Wave Doppler Radar Sensor for Detection of Vital Signs. Electronics 2019, 8, 561

by Jae-Hyun Park, Yeo-Jin Jeong, Ga-Eun Lee, Jun-Taek Oh and Jong-Ryul Yang

Electronics 2019, 8(8), 855; https://doi.org/10.3390/electronics8080855 - 31 Jul 2019

Cited by 4 | Viewed by 2052

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)

12 pages, 5376 KiB

Open AccessLetter

Elimination of Motion-Induced Phase Based on Double-Time Switching Scheme for SAA FMCW Radar

by Yi Lin, Kai Yang, Min Guo and Yunqi Fu

Electronics 2019, 8(7), 786; https://doi.org/10.3390/electronics8070786 - 14 Jul 2019

Cited by 3 | Viewed by 3022

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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