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IET RADAR SONAR AND NAVIGATION 2021年第7期15卷 686-696页

作者： AlShaya, Mohammed Yaghoobi, Mehrdad Mulgrew, Bernard Univ Edinburgh Inst Digital Commun Edinburgh Midlothian Scotland King Abdulaziz City Sci & Technol Natiotud Ctr Telecommun & Def Syst Technol Riyadh Saudi Arabia

An inter-range cell interference (IRCI)-free multiple subband multiple-input multiple-output (MIMO) synthetic aperture radar (SAR) algorithm is proposed to obtain a high-resolution wide swath (HRWS) imaging. The received signals of the proposed configuration are formulated as multiple-input single-output (MISO) system identification problems using the principle of the displaced phase centre in a way that all the subband waveforms are processed simultaneously without the need to separate them at the receiver. This would maximise the bandwidth utilisation efficiency. The channel impulse response in the range dimension is identified using a frequency domain system identification--based estimation algorithm, which is free from IRCI, instead of using conventional matched filters. A pulse repetition frequency lower than the Doppler bandwidth is used to obtain the HRWS imaging, and the resulted azimuth ambiguity is removed using a set of spatial filters applied on the received signals formulated as separate MISO system identification problems. Finally, both simulated and constructed raw data are used to validate the efficiency of the proposed algorithm.

关键词： spatial filters Electromagnetic compatibility and interference MISO system identification problems inter-range cell interference-free multiple subband multiple-input multiple-output synthetic aperture radar algorithm high-resolution wide swath imaging filtering methods in signal processing Modulation and coding methods IRCI-free multiple subband MIMO SAR radar interference Radio links and equipment multiple-input single-output system identification problems synthetic aperture radar radar imaging frequency domain system identification based estimation algorithm Radar equipment, systems and applications MISO communication MIMO radar

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Intelligent anti-epidemic mask based on KF and ECF fusion algorithm

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ELECTRONICS LETTERS 2021年第19期57卷 724-726页

作者： Xia, Kun Li, Xiang Li, Xueyong Liu, Yiren Zhang, Hongwei Hou, Ruifeng Univ Shanghai Sci & Technol Dept Elect Engn Shanghai Peoples R China

In response to environmental pollution and the spread of Coronavirus Disease 2019 (COVID-19), this paper proposes a new type of smart mask design, and specifically proposes an optimized double closed-loop control method, especially an improved filtering fusion algorithm. Using the filtering fusion algorithm proposed in this paper, after the Kalman filter (KF) filters the raw data of the attitude sensor, explicit complementary filtering and data fusion are used to obtain the attitude angle of the body. At the same time, the obtained attitude angle is combined with acceleration and blood oxygen concentration to obtain the behaviour characteristic value. On this basis, the speed of the oxygen supply fan captured by the photoelectric sensor is used to form a closed loop with the characteristic value of the behaviour. Finally, the structure of the mask is upgraded and optimized through fluid mechanics simulation, and experiments have verified that the combination of the replaceable filter cloth, the intelligent control system and the ultraviolet disinfection device can effectively protect people's health.

关键词： filtering methods in signal processing Biomedical measurement and imaging Digital signal processing Biomedical engineering Biology and medical computing

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Adaptive weighting for estimation of the mean of the merged measurement for multi-target bearing tracking

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ELECTRONICS LETTERS 2021年第10期57卷 412-414页

作者： Li, Quanrui Qiu, Longhao Qi, Bin Liang, Guolong Harbin Engn Univ Acoust Sci & Technol Lab Harbin 150001 Peoples R China Harbin Engn Univ Coll Underwater Acoust Engn Harbin 150001 Peoples R China Harbin Engn Univ Key Lab Marine Informat Acquisit & Secur Harbin 150001 Peoples R China Qingdao Haina Underwater Informat Technol Co Ltd Qingdao Peoples R China

In multi-target tracking, sensor with finite resolution generates merged measurements, which means that a group of targets might produce only one measurement, and such phenomenon could lead to degraded tracking performance if it is not considered. The generalised labelled multi-Bernoulli filter for merged measurement (GLMB-M) provides a promising solution for such problem. However, the merged measurement likelihood it used was modelled as a Gaussian density with its mean being the uniform weighted mean of the measurements generated by the merging targets. Such uniform weighting strategy might fail if the merged measurements deviate severely from the uniform weighted position due to significant difference of the strengths of the merging targets. To avoid such deviation, an adaptive weighting strategy for estimation of the mean of the merged bearing measurement is proposed, which uses the bearing measurement error to obtain the adaptive weighting factors. Simulation results show that the proposed adaptive weighting strategy outperforms the uniform weighting strategy when the strengths of the targets vary greatly, although both strategies provide similar performance when the strengths of the target are equal.

关键词： filtering methods in signal processing signal processing theory Other topics in statistics Other topics in statistics

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Deep unfolding based hyper-parameter optimisation for self-interference cancellation in LTE-A/5G-transceivers

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ELECTRONICS LETTERS 2021年第18期57卷 711-713页

作者： Motz, C. Paireder, T. Huemer, M. Johannes Kepler Univ Linz Christian Doppler Lab Digitally Assisted RF Trans Inst Signal Proc Linz Austria

Deep unfolding is a very promising concept that allows to combine the advantages of traditional estimation techniques, such as adaptive filters, and machine learning approaches, like artificial neural networks. Focusing on a challenging self-interference problem occurring in frequency-division duplex radio frequency transceivers, namely modulated spurs, it is shown that deep unfolding enables remarkable performance gains. Based on the hyper-parameter optimisation of several least-mean squares (LMS) variants and the recursive-least squares algorithm, the importance of a well-chosen loss function are highlighted. Especially the variable step-size LMS and the transform-domain LMS vastly benefit without increased runtime complexity.

关键词： Electromagnetic compatibility and interference filtering methods in signal processing Communication switching Mobile radio systems Optimisation techniques Interpolation and function approximation (numerical analysis) Digital signal processing Optimisation techniques Interpolation and function approximation (numerical analysis) Communications computing Neural nets

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Range-ambiguity suppression for noise radar in cluttered environment via sparse recovery

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ELECTRONICS LETTERS 2021年第23期57卷 894-896页

作者： Lu, Xingyu Yu, Wenchao Xia, Mengying Su, Weimin Gu, Hong Nanjing Univ Sci & Technol Sch Elect & Opt Engn Nanjing Peoples R China

Range ambiguity suppression is a significant problem in traditional pulse-Doppler radar systems, especially when the pulse repetition frequency is set high to avoid Doppler ambiguity. One possible way to deal with such problem is to apply the noise radar system, by transmitting pulse-agile waveforms and using a group of matched filters as the receiver to accumulate the power of unambiguous echoes while dispersing the range-ambiguous ones. However, when strong targets or heavy clutters exist, the dispersed ambiguous power is still high, which leads to high range-Doppler sidelobes and overwhelms the weak targets. This paper explores a new way to deal with the range-ambiguity suppression problem in noise radar. The range-ambiguity suppression as a sparse recovery problem is formulated, and then both the unambiguous and ambiguous targets (and/or clutters) can be simultaneously reconstructed. The proposed method can enhance the range-ambiguity suppression performance and synthetic an ambiguity-free range-Doppler map with a low sidelobe level, which ensures the weak target recovery performance even in a cluttered environment.

关键词： filtering methods in signal processing Radar theory Radar equipment, systems and applications

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Fractional-order complex correntropy algorithm for adaptive filtering in α-stable environment

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ELECTRONICS LETTERS 2021年第21期57卷 813-815页

作者： Qiu, Chen Dong, Zhenyuan Yan, Wenxing Qian, Guobing Southwest Univ Chongqing Key Lab Nonlinear Circuits & Intelligen Coll Elect & Informat Engn Chongqing 400715 Peoples R China

In adaptive filtering applications, the Gaussian distribution cannot be used to model the signal/noise with frequent spikes accurately. In fact, the rational model to simulate the behaviour of such signal/noise is the alpha-stable distribution process. In this letter, a fractional-order complex correntropy algorithm is proposed to deal with the case that both signal and noise processes are modelled as complex-valued alpha-stable signals. Compared with the classical approaches, the proposed fractional-order complex correntropy extends the Gaussian assumption of signal/noise in the complex domain to the assumption of alpha-stable distributions without second-order and higher order statistical moments. Benefitting from the fractional-order calculus and correntropy criterion, fractional-order complex correntropy shows great robustness to the jittery behaviour of complex-valued alpha-stable signal/noise. In addition, a convergence analysis for fractional-order complex correntropy has been carried out. Simulations on system identification revealed that the filtering performance is significantly improved by using fractional-order complex correntropy.

关键词： Other topics in statistics filtering methods in signal processing Other topics in statistics signal processing theory

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Consumer Wi-Fi device based action quality recognition: An illustrative example of seated dumbbell press action

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IET COMMUNICATIONS 2021年第4期15卷 613-626页

作者： Qin, Yuxi Pan, Su Zhou, Weiwei Pan, Duowei Li, Zibo Nanjing Univ Posts & Telecommun Key Lab Broadband Wireless Commun & Sensor Networ Minist Educ Nanjing Peoples R China Univ Calif Berkeley Coll Letter & Sci Berkeley CA 94720 USA

A system called WiSDP, which is based on Wi-Fi signals, to detect whether a Seated Dumbbell Press action is standard by using inexpensive consumer Wi-Fi devices is proposed. Compared with the scheme based on high speed cameras and wearable sensors, Wi-Fi devices are insensitive to light and colour, do not need wear any device, and decrease the risk of disclosing privacy. WiSDP senses environment changes through the Channel State Information which is fine-grained physical layer information comparing to frequently used Received signal Strength Indicator. Compared to the action recognition, action quality recognition depends on slight differences between a non-standard action and standard actions, which makes it challenging. The authors propose an improved sliding window algorithm calculating action energy to extract Seated Dumbbell Press actions from the Channel State Information streams, estimate action quality by choosing an appropriate classifier and use Principal Component Analysis and Butterworth low-pass filter to remove noise. The authors conduct experiments in two different scenarios and the average true positive rate of WiSDP are 94.66% and 95.11%, respectively.

关键词： filtering methods in signal processing Computer communications Radio links and equipment Digital signal processing Computer vision and image processing techniques Local area networks Principal component analysis Principal component analysis

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A novel secure diffusion Kalman filter algorithm against false data injection attacks

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IET COMMUNICATIONS 2021年第16期15卷 2028-2035页

作者： Du, Yanan Li, Ning Zhang, Yonggang Harbin Engn Univ Coll Intelligent Syst Sci & Engn Harbin 150001 Peoples R China

This paper proposes a novel secure diffusion Kalman filter (dKF) algorithm to improve the estimation performance crippled by false data injection attacks on sensors in wireless sensor networks (WSNs). Different from the conventional dKF, each adjacent node in the WSNs is detected to ascertain its trustworthiness before local estimate fusion, so as to form a new secure network topology. Then the combination step is performed to fuse the information collected from the secure topology. The proposed secure dKF algorithm, having a better estimation performance, is robust to false data injection attacks on multiple sensors and partial elements of measurements. For the proposed secure dKF algorithm, its mean and mean-square performance are derived, based on which its convergence is analysed. Additionally, the estimating and tracking problem of projectile position is investigated to confirm the effectiveness of the proposed secure dKF algorithm. It is shown by simulations that the proposed secure dKF algorithm achieves a significant estimation performance gain.

关键词： Interpolation and function approximation (numerical analysis) filtering methods in signal processing Communication network design, planning and routing Wireless sensor networks

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Mobile target localization and tracking techniques in harsh environment utilizing adaptive multi-modal data fusion

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IET COMMUNICATIONS 2021年第5期15卷 736-747页

作者： Mai, Zhenzhen Xiong, Hailiang Yang, Gangqiang Zhu, Weihong He, Fen Bian, Ruochen Li, Yujun Shandong Univ Sch Informat Sci & Engn Qingdao 266237 Peoples R China China Res Inst Radiowave Propagat Natl Key Lab Electromagnet Environm Qingdao Peoples R China

Multi-source cooperative positioning systems relying on federated filtering have become attractive development directions of navigation strategy in real-time localization and tracking under challenging urban environment. However, local Kalman filters of traditional federated filtering may result in divergence when the system model or the measurements is inaccurate, and the fixed information distribution coefficient in federated filter cannot adaptively reflect the performance of each local filter. To improve the precision and robustness of the integrated navigation system, a novel adaptive federated strong tracking Kalman filter with dynamic fading factor mechanism for multi-sensor information fusion is proposed. Through iterative computation of the fading factor and updating the adaptive weight coefficients, strong tracking filter becomes robust to the uncertainty of system model. Meanwhile, an effective adaptive information distribution estimation algorithm based on the predicted residuals is constructed to balance the contributions of the kinematic model information and measurements on the state estimates. To ensure the stability of filtering, a simplified fusion strategy is established to solve the singular problem of the global covariance matrix of estimation error. Theoretical analysis and simulation results demonstrate the validity of the proposed approach in improving the accuracy and robustness of the integrated navigation and positioning systems. The proposed integrated multi-modal cooperative navigation and positioning algorithm will be of great significance to the implementation of real-time mobile target localization and tracking in harsh environment or dead zone.

关键词： filtering methods in signal processing Mobile radio systems Radionavigation and direction finding Linear algebra (numerical analysis)

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Achieving the performance of the MMSE receiver with the maximum ratio combiner

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IET COMMUNICATIONS 2021年第20期15卷 2513-2525页

作者： Carrera, Diego Fernando Vargas-Rosales, Cesar Azpilicueta, Leyre Granda, Fausto Univ Tecn Particular Loja Dept Comp Sci & Elect Loja Ecuador Tecnol Monterrey Sch Engn & Sci Monterrey NL Mexico Univ Fuerzas Armadas ESPE Elect & Elect Engn Dept Sangolqui Ecuador

In this article, we propose a new pilot mapping method to jointly estimate the channel state information of the user while reducing the interference effects of multiuser multicell mobile scenarios. The problem of achieving the wireless performance of the minimum mean square error (MMSE) receiver with the maximum ratio (MR) combiner for massive multiple-input multiple-output (MIMO) systems in the frequency bands of 2.5 GHz and 28 GHz is addressed. By transmitting fewer pilots in the uplink communications and arranging those pilots to reduce interuser interference, we can achieve higher spectral efficiency (SE) with the MR and MMSE receivers. Numerical results show significantly fewer floating-point operations for MIMO processing when the proposed pilot mapping strategy is combined with Kalman filtering estimation and MR processing, achieving an SE comparable to the MMSE receiver.

关键词： Electromagnetic compatibility and interference filtering methods in signal processing Communication channel equalisation and identification Mobile radio systems Other topics in statistics Interpolation and function approximation (numerical analysis)

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