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UGV-UAV robust cooperative positioning algorithm with object detection

IET INTELLIGENT TRANSPORT SYSTEMS 2021年第7期15卷 851-862页

作者： Wang, Dongjia Lian, Baowang Tang, Chengkai Northwestern Polytech Univ Sch Elect & Informat YouYi West Rd 127 Xian Peoples R China

Traditional Global Navigation Satellite Systems (GNSS) experience their limitations in urban canyons. However, it is significant to improve the accuracy of positioning with the rapid development of smart cities. To solve this problem, a UGV-UAV robust cooperative positioning algorithm with object detection is proposed, which utilises an unmanned aerial vehicle (UAV) to assist an unmanned ground vehicle (UGV) to achieve accurate positioning. When the UAV is in the sky with a good reception of satellite signals, the UGV uses the YOLOv3 object detection method to detect the UAV in images captured by camera, and acquires visual measurements including angles and ranges of the ground camera relative to the UAV through the proposed monocular vision measuring with object detection (ODMVM) model. Then, in order to solve the problem that visual measurement is disturbed by the real world, a robust Kalman filter is introduced that integrates measurements from available GNSS, inertial measurement unit (IMU), monocular camera, and the position broadcast of cooperative UAV to obtain more robust and accurate position estimation. Experimental and simulation results show that the proposed cooperation positioning algorithm can improve the positioning accuracy by 73.63% compared with the traditional cooperation positioning algorithm in urban canyons.

关键词： Optical, image and video signal processing filtering methods in signal processing Radionavigation and direction finding Image sensors Spatial variables control Aerospace control Mobile robots Telerobotics Computer vision and image processing techniques Other topics in statistics

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Adaptive comprehensive particle swarm optimisation-based functional-link neural network filtre model for denoising ultrasound images

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IET IMAGE processing 2021年第6期15卷 1232-1246页

作者： Kumar, Manish Mishra, Sudhansu Kumar Joseph, Justin Jangir, Sunil Kumar Goyal, Dinesh Mody Univ Sci & Technol Dept Elect & Biomed Engn Sikar 322311 India Birla Inst Technol Dept Elect & Elect Engn Ranchi Bihar India Indian Inst Technol Dept Elect Engn Gandhinagar India Poornima Inst Engn Technol Dept Comp Sci & Engn Jaipur Rajasthan India

Multiplicative speckle is a dominant type of noise that spoils the inherent features of the medical ultrasound (US) images. Apart from the speckle, impulse and Gaussian noises also appear in the US image due to the error encountered during the data transmission and transition of switching circuits and sensors. The noise not only deteriorates the visual quality of the US but also creates complications in the diagnosis. In this study, an adaptive comprehensive particle swarm optimisation-based functional-link neural network (ACPSO-FLNN) filtre has been proposed and implemented in filtering noisy US images in different noise conditions. The proposed filtre is compared with some state-of-the-art filtering techniques. Quantitative and qualitative measures such as training time, time complexity, convergence rate, and statistical test are included to study the performance of the proposed filtre. Furthermore, sensitivity, computational complexity, and order of the proposed filtre are also investigated. Friedman's test with 50 images is performed for statistical validation. The lower rank, that is, 6 and critical value of 21 x 10-4 of the proposed ACPSO-FLNN filtre validates its dominance over other filtres.

关键词： Sonic and ultrasonic radiation (medical uses) Patient diagnostic methods and instrumentation Other topics in statistics Optimisation techniques Optical, image and video signal processing filtering methods in signal processing Sonic and ultrasonic radiation (biomedical imaging/measurement) Other topics in statistics Optimisation techniques Computer vision and image processing techniques Biology and medical computing

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Adaptive invariant Kalman filtering for attitude estimation on SO(3) thorough feedback calibration of prior error covariance

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IET CONTROL THEORY AND APPLICATIONS 2021年第14期15卷 1906-1914页

作者： Wang, Jiaolong Li, Minzhe Jiangnan Univ Inst Automat Minist Educ Key Lab Adv Proc Control Light Ind Wuxi Jiangsu Peoples R China Shanghai Jiao Tong Univ Sch Aeronaut & Astronaut Shanghai Peoples R China

For invariant attitude dynamics evolving on matrix Lie groups, by proposing the stochastic feedback-based covariance calibration scheme, an adaptive invariant Kalman filter (AIKF) is elaborated to deal with the attitude estimation problems corrupted by unknown or inaccurate process noise statistics. The invariant Kalman filter (IKF) takes into account the geometry property of attitude dynamics and can boost the estimation performance;however, IKF requires accurate knowledge of the noise statistics and an incorrect noise parameter is prone to deteriorating the precision of final estimates. To eliminate this impact, instead of using the original covariance propagation step of IKF, the prior error covariance of the proposed AIKF is online calibrated based on the posterior information of the feedback stochastic sequence. As the main advantage, the statistics parameter of system process noise is no longer required in the proposed AIKF and the negative influence by unknown/incorrect noise parameters can be reduced significantly. The mathematical foundation for the new adaption scheme of AIKF is also presented. The AIKF's advantage in filtering adaptability and simplicity is further demonstrated by numerical simulations.

关键词： signal processing theory system process noise stochastic processes Other topics in statistics stochastic systems Kalman filters state-space methods geometry property statistics parameter AIKF Combinatorial mathematics calibration Time-varying control systems invariant attitude dynamics stochastic feedback-based covariance calibration scheme attitude estimation problems covariance matrices Lie groups feedback Algebra feedback calibration adaptive invariant kalman filter filtering methods in signal processing covariance propagation step unknown process noise statistics error covariance geometry matrix Lie groups feedback stochastic sequence attitude control

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Robust state estimation for uncertain linear discrete systems with d-step state delay

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IET CONTROL THEORY AND APPLICATIONS 2021年第13期15卷 1708-1723页

作者： Wang, Jing Mao, Yao Li, Ziqiang Gao, Junwei Liu, Huabo Qingdao Univ Sch Automat Qingdao 266071 Peoples R China Qingdao Univ Inst Future Qingdao Peoples R China Shandong Key Lab Ind Control Technol Qingdao Peoples R China Chinese Acad Sci Key Lab Opt Engn Chengdu Peoples R China Chinese Acad Sci Inst Opt & Elect Chengdu Peoples R China Univ Chinese Acad Sci Beijing Peoples R China

This paper discusses the state estimation problems of an uncertain linear discrete time-varying state space model with d-step state delay. Based on the principle of minimising the expectation of estimation errors and the method of state augmentation, a robust state estimation algorithm is proposed. Specially, this estimator retains the form of Kalman-like filter and the characteristics of fast recursive calculation. Moreover, the conditions of bounded estimation error covariance and the proof of asymptotic unbiasedness of the filter are given. Finally, numerical examples are used to verify the effectiveness and the wide applicability of this estimator.

关键词： filtering methods in signal processing Simulation, modelling and identification Other topics in statistics Algebra Other topics in statistics Linear control systems Control system analysis and synthesis methods Stability in control theory Discrete control systems

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Shaped offset 8PSK and coded shaped offset 8PSK with improved spectrum efficiency for satellite communication

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IET COMMUNICATIONS 2021年第2期15卷 305-316页

作者： Liu, Yue Cao, Ning Mao, Minghe Li, Gang Hohai Univ Sch Comp & Informat Nanjing Peoples R China Minist Water Resources Peoples Republ China Informat Ctr Beijing Peoples R China

The development of satellite communication (SATCOM) puts forward demanding requirements for the modulation methods' spectral efficiency (SE) which is mainly subject to the pulse shaping and the utilisation of signal space. To date, there has rare consideration on the modification of high order phase shift keying (HOPSK) to gain higher SE in this literature. In this work, shaped offset 8PSK (SO8PSK) is developed which splits 8PSK bit transmission into three offset paths and then loads the shaping pulse onto them. The obtained modulation with continuous constrained phase and constant envelope is shown to increase the SE compared to 8PSK by about 43% and is applicable for the nonlinear and band-limited SATCOM environment. To address the HOPSK inherent complexity, a simplified receiver is provided to reduce about two-third matched filters. Additionally, the iterative encoding of SO8PSK is presented and it is used as the inner code of serial concatenated coding (SCC) . This modification method can be seen as a starting point to the better use of HOPSK for SATCOM.

关键词： Codes filtering methods in signal processing Satellite communication systems Interpolation and function approximation (numerical analysis)

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Learning near-optimal broadcasting intervals in decentralized multi-agent systems using online least-square policy iteration

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IET CONTROL THEORY AND APPLICATIONS 2021年第8期15卷 1054-1067页

作者： Palunko, Ivana Tolic, Domagoj Prkacin, Vicko Univ Dubrovnik LARIAT Lab Intelligent Autonomous Syst Cira Carica 4 Dubrovnik Croatia RIT Croatia LARIAT Lab Intelligent Autonomous Syst Dubrovnik Croatia

Here, agents learn how often to exchange information with neighbours in cooperative multi-agent systems (MASs) such that their linear quadratic regulator (LQR)-like performance indices are minimized. The investigated LQR-like cost functions capture trade-offs between the energy consumption of each agent and MAS local control performance in the presence of exogenous disturbances, delayed and noisy data. Agent energy consumption is critical for prolonging the MAS mission and is composed of both control (e.g. acceleration, velocity) and communication efforts. Taking provably stabilizing upper bounds on broadcasting intervals as optimization constraints, an online off-policy model-free learning algorithm based on least square policy iteration (LSPI) to minimize the cost function of each agent is employed. Consequently, the obtained broadcasting intervals adapt to the most recent information (e.g. delayed and noisy agents' inputs and/or outputs) received from neighbours whilst provably stabilize the MAS. Chebyshev polynomials are utilized as the approximator in the LSPI whereas Kalman filtering handles sampled, corrupted, and delayed data. Subsequently, convergence and near-optimality of our LSPI scheme are inspected. The proposed methodology is verified experimentally using an inexpensive motion capture system and nano quadrotors.

关键词： filtering methods in signal processing Optimisation techniques signal processing theory Interpolation and function approximation (numerical analysis) Optimisation techniques Interpolation and function approximation (numerical analysis) Stability in control theory Optimal control Multivariable control systems Self-adjusting control systems

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An EKF based overlapping coalition formation game for cooperative wireless network navigation

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IET COMMUNICATIONS 2021年第19期15卷 2407-2424页

作者： Ke, Mingxing Tian, Shiwei Tong, Kaixiang Zhang, Haiyan Natl Univ Def Technol Coll Elect Countermeasures Hefei Peoples R China PLA Army Engn Univ Coll Commun Engn Nanjing Peoples R China

The problem of efficient link selections for cooperative navigation is investigated in dynamic wireless networks, using an extended Kalman filter based overlapping coalition formation (OCF) game approach. Due to the densely deployment of nodes without proper link selections, the conventional cooperative navigation approaches usually yield high time-frequency resources as the existing resource management methods only work properly in static localisation systems. A new link selection mechanism which is reliable with limited resources in dynamic positioning scenarios is proposed. The varying topological structure and states of every node will be taken into consideration while each node abandons a considerable number of unnecessary links. Firstly, the state of every mobile node will be estimated in real-time. Then a selection criterion is applied to determine whether nodes are well navigated. If the criterion is satisfied, an OCF game will be employed to construct the effective link selection. Otherwise, a re-link mechanism will be used to obtain precise state information of each node. Numerical results show that the cooperative navigation algorithm can significantly improve the positioning accuracy and the proposed OCF game approach can build a cooperative network with limited number of links at the cost of appropriate performance degradation.

关键词： filtering methods in signal processing Radio links and equipment Game theory

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Complementary frequency modulated radar waveforms and optimised receive processing

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IET RADAR SONAR AND NAVIGATION 2021年第7期15卷 708-723页

作者： Jones, Christian C. Mohr, Charles A. McCormick, Patrick M. Blunt, Shannon D. Univ Kansas Radar Syst Lab RSL Lawrence KS 66045 USA US Air Force Res Lab AFRL Sensors Directorate Wright Patterson AFB OH USA

Design methodologies are developed for complementary frequency modulated (FM) waveforms and for optimised complementary mismatched filtering (MMF) of arbitrary non-repeating waveforms. The former is a sub-class of random FM waveforms denoted as complementary FM (Comp-FM) while the latter extends a practical instantiation of least-squares mismatched filtering yielding the mismatched complementary-on-receive filtering (MiCRFt) scheme. Both of these approaches have an emphasis on the non-ideal physical effects of the radar transmitter and receiver, thereby permitting high-fidelity simulation analysis and subsequent experimental demonstration of their efficacy using open-air measurements.

关键词： radar signal processing radar transmitter radar transmitters nonrepeating waveforms filtering scheme optical modulation nonideal physical effects Comp-FM optimised complementary mismatched filtering optimisation Radar equipment, systems and applications receiver random FM filtering methods in signal processing frequency modulation design methodologies Interpolation and function approximation (numerical analysis) complementary frequency modulated radar waveforms complementary FM FM radar filtering theory

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A two-stage method for bus passenger load prediction using automatic passenger counting data

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IET INTELLIGENT TRANSPORT SYSTEMS 2021年第2期15卷 248-260页

作者： Wang, Pengfei Chen, Xuewu Chen, Jingxu Hua, Mingzhuang Pu, Ziyuan Southeast Univ Sch Transportat Jiangsu Prov Collaborat Innovat Ctr Modern Urban Jiangsu Key Lab Urban ITS Nanjing 211189 Peoples R China Monash Univ Sch Engn Jalan Lagoon Selatan Bandar Sunway 47500 Malaysia

In high-frequency transit, providing real-time crowding information (RTCI) is a potential way to promote passenger satisfaction and reduce negative crowding externalities, by assisting passengers in choosing less crowded vehicles. To make RTCI convincing and reliable, it is necessary to provide predictive RTCI, in which bus passenger load (BPL) prediction is the primary problem. This paper proposes a novel two-stage BPL prediction method using automatic passenger counting (APC) data. The first stage is to predict short-term passenger flows at stops based on an adaptive Kalman filter approach. Using the outputs from the first stage as well as other variables directly from APC data, the second stage is to predict BPL based on a support vector regression algorithm. Several methods from the existing literature are used as benchmarks to test the relative performance of the proposed method. An empirical study on bus line 1 in Suzhou, China shows that the proposed method outperforms all the benchmarks, and shows significant superiority over other methods for stops with sharp increases in BPL and for multi-step ahead prediction. This study contributes to the limited literature on BPL prediction and lays the foundation for providing accurate and reliable predictive RTCI in the future.

关键词： filtering methods in signal processing Digital signal processing Traffic engineering computing Regression analysis Regression analysis Support vector machines

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Smart pansharpening approach using kernel-based image filtering

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IET IMAGE processing 2021年第11期15卷 2629-2642页

作者： Al Smadi, Ahmad Yang, Shuyuan Mehmood, Atif Abugabah, Ahed Wang, Min Bashir, Muzaffar Xidian Univ Sch Artificial Intelligence 2 South Taibai Rd Xian 710071 Peoples R China Zayed Univ Coll Technol Innovat Abu Dhabi U Arab Emirates Xidian Univ Key Lab Radar Signal Proc Xian Peoples R China Univ Punjab Dept Phys Lahore Pakistan

Remote sensing image fusion plays important roles in numerous applications, including monitoring, metrology, and agriculture. Image fusion gathers essential information from several image sources and consolidates them into a single image called a fused image. The fused image involves relevant data, and it is more informative than any other images extracted from one source. This study proposed a pansharpening technique based on image filtering utilising a bilateral filter to generate high-frequency details from panchromatic image. The various types of side window guided filters are employed to enhance the multispectral band from panchromatic image and then used these filters to adjust spatial data misfortune that happens when images are combined. Experimental results demonstrated that the proposed method provides consistent results concise with reported by the previous research in terms of subjective and objective assessments on remote sensing data.

关键词： image resolution remote sensing data pansharpening technique filtering methods in signal processing image colour analysis image filtering panchromatic image sensing image fusion Computer vision and image processing techniques image fusion remote sensing geophysical image processing image fusion gathers essential information Optical, image and video signal processing single image fused image filtering theory Instrumentation and techniques for geophysical, hydrospheric and lower atmosphere research smart pansharpening approach image sources bilateral filter side window guided filters

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