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12 pages, 2375 KiB

Open AccessArticle

Effect of Structural Uncertainty in Passive Microwave Soil Moisture Retrieval Algorithm

by Lanka Karthikeyan, Ming Pan, Dasika Nagesh Kumar and Eric F. Wood

Sensors 2020, 20(4), 1225; https://doi.org/10.3390/s20041225 - 24 Feb 2020

Cited by 5 | Viewed by 2820

Passive microwave sensors use a radiative transfer model (RTM) to retrieve soil moisture (SM) using brightness temperatures (T_B) at low microwave frequencies. Vegetation optical depth (VOD) is a key input to the RTM. Retrieval algorithms can analytically invert the RTM [...] Read more.

Passive microwave sensors use a radiative transfer model (RTM) to retrieve soil moisture (SM) using brightness temperatures (T_B) at low microwave frequencies. Vegetation optical depth (VOD) is a key input to the RTM. Retrieval algorithms can analytically invert the RTM using dual-polarized T_B measurements to retrieve the VOD and SM concurrently. Algorithms in this regard typically use the τ-ω types of models, which consist of two third-order polynomial equations and, thus, can have multiple solutions. Through this work, we find that uncertainty occurs due to the structural indeterminacy that is inherent in all τ-ω types of models in passive microwave SM retrieval algorithms. In the process, a new analytical solution for concurrent VOD and SM retrieval is presented, along with two widely used existing analytical solutions. All three solutions are applied to a fixed framework of RTM to retrieve VOD and SM on a global scale, using X-band Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) T_B data. Results indicate that, with structural uncertainty, there ensues a noticeable impact on the VOD and SM retrievals. In an era where the sensitivity of retrieval algorithms is still being researched, we believe the structural indeterminacy of RTM identified here would contribute to uncertainty in the soil moisture retrievals. Full article

(This article belongs to the Special Issue Radar and Radiometric Sensors and Sensing)

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31 pages, 11407 KiB

Open AccessArticle

Constrained Transmit Beampattern Design Using a Correlated LFM-PC Waveform Set in MIMO Radar

by Sheng Hong, Yantao Dong, Rui Xie, Yu Ai and Yuhao Wang

Sensors 2020, 20(3), 773; https://doi.org/10.3390/s20030773 - 31 Jan 2020

Cited by 5 | Viewed by 2181

Abstract

This paper considers the design of a desired transmit beampattern under the good ambiguity function constraint using a correlated linear frequency modulation-phase coded (LFM-PC) waveform set in multiple-input-multiple-output (MIMO) radar. Different from most existing beampattern design approaches, we propose using the LFM-PC waveform [...] Read more.

This paper considers the design of a desired transmit beampattern under the good ambiguity function constraint using a correlated linear frequency modulation-phase coded (LFM-PC) waveform set in multiple-input-multiple-output (MIMO) radar. Different from most existing beampattern design approaches, we propose using the LFM-PC waveform set to conquer the challenging problem of synthesizing waveforms with constant-envelope and easy-generation properties, and, meanwhile, solve the hard constraint of a good ambiguity behaviour. First, the ambiguity function of the LFM-PC waveform set is derived, and the superiority of LFM-PC waveforms over LFM and PC waveforms is verified. The temporal and spatial characteristic analysis of the LFM-PC waveform set demonstrates that both the transmit beampattern and sidelobe level are mainly affected by the frequency intervals, bandwidths, and phase-coded sequences of the LFM-PC waveform set. Finally, the constrained beampattern design problem is formulated by optimizing these parameters for desired beampatterns and low sidelobes at different doppler frequencies, which is a bi-objective optimization problem. To solve this, we propose a joint optimization strategy followed by a mandatory optimization, where the sequence quadratic programming (SQP) algorithm and adaptive clonal selection (ACS) algorithm are exploited iteratively. The simulation results demonstrate the efficiency of our proposed method. Full article

(This article belongs to the Special Issue Radar and Radiometric Sensors and Sensing)

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20 pages, 870 KiB

Open AccessArticle

Joint Optimization of Transmit Waveform and Receive Filter with Pulse-to-Pulse Waveform Variations for MIMO GMTI

by Zhoudan Lv, Feng He, Zaoyu Sun and Zhen Dong

Sensors 2019, 19(24), 5575; https://doi.org/10.3390/s19245575 - 17 Dec 2019

Viewed by 2651

Abstract

Multi-input multi-output (MIMO) is usually defined as a radar system in which the transmit time and receive time, space and transform domain can be separated into multiple independent signals. Given the bandwidth and power constraints of the radar system, MIMO radar can improve [...] Read more.

Multi-input multi-output (MIMO) is usually defined as a radar system in which the transmit time and receive time, space and transform domain can be separated into multiple independent signals. Given the bandwidth and power constraints of the radar system, MIMO radar can improve its performance by optimize design transmit waveforms and receive filters, so as to achieve better performance in suppressing clutter and noise. In this paper, we cyclicly optimize the transmit waveform and receive filters, so as to maximize the output signal interference and noise ratio (SINR). From fixed pulse-to-pulse waveform to pulse-to-pulse waveform variations, we discuss the joint optimization under energy constraint, then extend it to optimizations under constant-envelope constraint and similarity constraint. Compared to optimization with fixed pulse-to-pulse waveform, the generalized optimization achieves higher output SINR and lower minimum detectable velocity (MDV), further improve the suppressing performance. Full article

(This article belongs to the Special Issue Radar and Radiometric Sensors and Sensing)

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24 pages, 2027 KiB

Open AccessArticle

Review-Microwave Radar Sensing Systems for Search and Rescue Purposes

by Nguyen Thi Phuoc Van, Liqiong Tang, Veysel Demir, Syed Faraz Hasan, Nguyen Duc Minh and Subhas Mukhopadhyay

Sensors 2019, 19(13), 2879; https://doi.org/10.3390/s19132879 - 28 Jun 2019

Cited by 42 | Viewed by 9335

Abstract

This paper presents a survey of recent developments using Doppler radar sensor in searching and locating an alive person under debris or behind a wall. Locating a human and detecting the vital signs such as breathing rate and heartbeat using a microwave sensor [...] Read more.

This paper presents a survey of recent developments using Doppler radar sensor in searching and locating an alive person under debris or behind a wall. Locating a human and detecting the vital signs such as breathing rate and heartbeat using a microwave sensor is a non-invasive technique. Recently, many hardware structures, signal processing approaches, and integrated systems have been introduced by researchers in this field. The purpose is to enhance the accuracy of vital signs’ detection and location detection and reduce energy consumption. This work concentrates on the representative research on sensing systems that can find alive people under rubble when an earthquake or other disasters occur. In this paper, various operating principles and system architectures for finding survivors using the microwave radar sensors are reviewed. A comparison between these systems is also discussed. Full article

(This article belongs to the Special Issue Radar and Radiometric Sensors and Sensing)

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17 pages, 8069 KiB

Open AccessArticle

OFDM Chirp Waveform Design Based on Subchirp Bandwidth Overlap and Segmented Transmitting for Low Correlation Interference in MIMO Radar

by Xiang Lan, Min Zhang and Jin-Xing Li

Sensors 2019, 19(12), 2696; https://doi.org/10.3390/s19122696 - 14 Jun 2019

Cited by 7 | Viewed by 3543

Abstract

There are some special merits for the orthogonal frequency division multiplexing (OFDM) chirp waveform as multiple input multiple output (MIMO) signals. This signal has high range resolution, good Doppler tolerance, and constant modulus superiority since it exploits a full bandwidth and is based [...] Read more.

There are some special merits for the orthogonal frequency division multiplexing (OFDM) chirp waveform as multiple input multiple output (MIMO) signals. This signal has high range resolution, good Doppler tolerance, and constant modulus superiority since it exploits a full bandwidth and is based on chirp signals. The correlation sidelobe peaks level are critical for the detection requirement of MIMO radar signals, however conventional OFDM chirp signals produce high autocorrelation sidelobe peaks (ASP) and cross-correlation peaks (CP), which reduces detection performance. In this paper, we explore the structure of OFDM chirp signals’ autocorrelation function and proposed a scheme to reduce the designed signal’s ASP by a designing suitable range of subchirp bandwidth and a segmented transmit-receive mode. Next, we explore a suitable range of interval between the chirp rates of each two signals to reduce the CP. The simulation of designed signals verifies the effectiveness of the proposed methods in the reduction of ASP and CP, with the correlation performance being compared with recent relate studies. In addition, the multiple signals detection and one-dimensional range image simulation show the good detection performance of a designed signal in MIMO radar detection. Full article

(This article belongs to the Special Issue Radar and Radiometric Sensors and Sensing)

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13 pages, 3703 KiB

Open AccessArticle

A 1-GHz 64-Channel Cross-Correlation System for Real-Time Interferometric Aperture Synthesis Imaging

by Xiangzhou Guo, Muhammad Asif, Anyong Hu, Zhiping Li and Jungang Miao

Sensors 2019, 19(7), 1739; https://doi.org/10.3390/s19071739 - 11 Apr 2019

Cited by 12 | Viewed by 3710

Abstract

We present a 64-channel 1-bit/2-level cross-correlation system for a passive millimeter wave imager used for indoor human body security screening. Sixty-four commercial comparators are used to perform 1-bit analog-to-digital conversion, and a Field Programmable Gate Array (FPGA) is used to perform the cross-correlation [...] Read more.

We present a 64-channel 1-bit/2-level cross-correlation system for a passive millimeter wave imager used for indoor human body security screening. Sixty-four commercial comparators are used to perform 1-bit analog-to-digital conversion, and a Field Programmable Gate Array (FPGA) is used to perform the cross-correlation processing. This system can handle 2016 cross-correlations at the sample frequency of 1GHz, and its power consumption is 48.75 W. The data readout interface makes it possible to read earlier data while simultaneously performing the next correlation when imaging at video rate. The longest integration time is up to 68.7 s, which can satisfy the requirements of video rate imaging and system calibration. The measured crosstalk between neighboring channels is less than 0.068%, and the stability is longer than 10 s. A correlation efficiency greater than 96% is achieved for input signal levels greater than −25 dBm. Full article

(This article belongs to the Special Issue Radar and Radiometric Sensors and Sensing)

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11 pages, 5113 KiB

Open AccessArticle

On the Use of Microwave Holography to Detect Surface Defects of Rails and Measure the Rail Profile

by Andrey Zhuravlev, Vladimir Razevig, Sergey Ivashov, Aleksey Skrebkov and Viktor Alekseev

Sensors 2019, 19(6), 1376; https://doi.org/10.3390/s19061376 - 19 Mar 2019

Cited by 7 | Viewed by 2849

Abstract

The use of microwave holography for detecting rail surface defects is considered in this paper. A brief review of available sources on radar methods for detecting defects on metal surfaces and rails is given. An experimental setup consisting of a two-coordinate electromechanical scanner [...] Read more.

The use of microwave holography for detecting rail surface defects is considered in this paper. A brief review of available sources on radar methods for detecting defects on metal surfaces and rails is given. An experimental setup consisting of a two-coordinate electromechanical scanner and a radar with stepped frequency signal in the range from 22.2 to 26.2 GHz is described, with the help of which experimental data were obtained. Fragments of R24 rails with surface defects in their heads were used as the object of study. The radar images of rail defects were obtained by the described method based on back propagation of a wavefront. It is shown that polarization properties of electromagnetic waves can be used to increase the contrast of small-scale surface defects. A method of estimating rail surface profile by radar measurements is given and applied to the experimental data. Comparison of the longitudinal rail head profiles obtained by radar and by direct contact measurements showed that the radar method gives comparable accuracy. Full article

(This article belongs to the Special Issue Radar and Radiometric Sensors and Sensing)

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16 pages, 6954 KiB

Open AccessArticle

Statistical Approach to Spectrogram Analysis for Radio-Frequency Interference Detection and Mitigation in an L-Band Microwave Radiometer

by Myeonggeun Oh and Yong-Hoon Kim

Sensors 2019, 19(2), 306; https://doi.org/10.3390/s19020306 - 14 Jan 2019

Cited by 5 | Viewed by 3860

Abstract

For the elimination of radio-frequency interference (RFI) in a passive microwave radiometer, the threshold level is generally calculated from the mean value and standard deviation. However, a serious problem that can arise is an error in the retrieved brightness temperature from a higher [...] Read more.

For the elimination of radio-frequency interference (RFI) in a passive microwave radiometer, the threshold level is generally calculated from the mean value and standard deviation. However, a serious problem that can arise is an error in the retrieved brightness temperature from a higher threshold level owing to the presence of RFI. In this paper, we propose a method to detect and mitigate RFI contamination using the threshold level from statistical criteria based on a spectrogram technique. Mean and skewness spectrograms are created from a brightness temperature spectrogram by shifting the 2-D window to discriminate the form of the symmetric distribution as a natural thermal emission signal. From the remaining bins of the mean spectrogram eliminated by RFI-flagged bins in the skewness spectrogram for data captured at 0.1-s intervals, two distribution sides are identically created from the left side of the distribution by changing the standard position of the distribution. Simultaneously, kurtosis calculations from these bins for each symmetric distribution are repeatedly performed to determine the retrieved brightness temperature corresponding to the closest kurtosis value of three. The performance is evaluated using experimental data, and the maximum error and root-mean-square error (RMSE) in the retrieved brightness temperature are served to be less than approximately 3 K and 1.7 K, respectively, from a window with a size of 100 × 100 time–frequency bins according to the RFI levels and cases. Full article

(This article belongs to the Special Issue Radar and Radiometric Sensors and Sensing)

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