Contact Dr Mengwei Sun
Areas of expertise
- Autonomous Systems
- Computing, Simulation & Modelling
- Sensor Technologies
Background
Dr Mengwei Sun is a Lecturer in Sensor Fusion at Cranfield University, specialising in statistical signal processing, focusing on target tracking, navigation, multi-sensor data fusion, and Bayesian inference for autonomous systems. She has published 18 peer-reviewed journal articles (9 as first author), 16 conference papers (including three best paper awards), and four patents. With a strong research track record, her work has made a significant impact in both academia and industry, collaborating with companies such as Telespazio, GMV, and Spirent.
Research opportunities
Dr Sun's research focuses on sensor fusion, Bayesian inference, and machine learning for target tracking and navigation. Her key areas of expertise include:
- Multi-sensor data fusion for autonomous systems.
- Bayesian filtering and deep learning for aerospace and defence applications.
- Scalable inference in sensor networks for real-time decision-making.
- Alternative positioning techniques for maritime and aerial navigation.
- Kernel-based methods and adaptive filtering for enhanced tracking performance.
Her research has been applied in air traffic management, maritime navigation, and defence surveillance, with an emphasis on bridging theoretical advancements with real-world applications.
Current activities
Dr Sun is actively engaged in cutting-edge research and academic leadership, including:
- Developing advanced Bayesian and deep learning-based tracking techniques for air traffic and maritime navigation.
- Leading research initiatives such as the ESA-funded MANAA project on alternative positioning for autonomous maritime vehicles.
- Supervising MSc and PhD students in collaboration with industry partners like Lockheed Martin, GMV, and BAE Systems.
- Serving as a reviewer for leading IEEE journals and conferences, contributing to advancements in signal processing and autonomous systems research.
Clients
- Spirent Communications plc
- BAE Systems PLC
- Lockheed Martin Corporation
- Defence Science and Technology Laboratory
- MBDA UK Ltd
Publications
Articles In Journals
- Sun M, Davies ME, Proudler IK & Hopgood JR. (2023). Adaptive Kernel Kalman Filter. IEEE Transactions on Signal Processing, 71
- Sun M, Davies ME, Proudler IK & Hopgood JR. (2022). Adaptive Kernel Kalman Filter Based Belief Propagation Algorithm for Maneuvering Multi-Target Tracking. IEEE Signal Processing Letters, 29
- Sun M, Goussetis G, Xu K, Ding Y, Mclaughlin S, .... (2022). Joint Digital Analogue DVB-S2(X) Link Optimization in Non-Linear Channel. IEEE Access, 10
- Liu H, Yang X, Chen P, Sun M, Li B, .... (2020). Deep Learning Based Nonlinear Signal Detection in Millimeter-Wave Communications. IEEE Access, 8
- Sun M, Ding Y & Goussetis G. (2020). Wireless‐powered CR‐IoT with ambient backscattering: a new transmission mode. IET Communications, 14(22)
- Sun M, Wang X, Zhao C, Li B, Liang Y-C, .... (2018). Adaptive Sensing Schedule for Dynamic Spectrum Sharing in Time-Varying Channel. IEEE Transactions on Vehicular Technology, 67(6)
- Chu Z, Zhou F, Zhu Z, Sun M & Al-Dhahir N. (2017). Energy Beamforming Design and User Cooperation for Wireless Powered Communication Networks. IEEE Wireless Communications Letters, 6(6)
- Li S, Sun M, Liang Y-C, Li B & Zhao C. (2017). Spectrum Sensing for Cognitive Radios With Unknown Noise Variance and Time-variant Fading Channels. IEEE Access, 5
- Li B, Sun M, Wang S, Guo W & Zhao C. (2016). Low-Complexity Noncoherent Signal Detection for Nanoscale Molecular Communications. IEEE Transactions on NanoBioscience, 15(1)
- Li B, Sun M, Wang S, Guo W & Zhao C. (2016). Local Convexity Inspired Low-Complexity Noncoherent Signal Detector for Nanoscale Molecular Communications. IEEE Transactions on Communications, 64(5)
- Sun M, Zhao C, Yan S & Li B. (2016). A Novel Spectrum Sensing for Cognitive Radio Networks with Noise Uncertainty. IEEE Transactions on Vehicular Technology, 66(5)
- Li B, Zhao C, Sun M, Zhang H, Zhou Z, .... (2015). A Bayesian Approach for Nonlinear Equalization and Signal Detection in Millimeter-Wave Communications. IEEE Transactions on Wireless Communications, 14(7)
- Sun M, Li S, Li B & Zhao C. (2015). Spectrum Sensing for Self-Organizing Network in the Presence of Time-Variant Multipath Flat Fading Channels and Unknown Noise Variance. Mobile Networks and Applications, 20(4)
- Li B, Sun M, Li X, Nallanathan A & Zhao C. (2015). Energy Detection Based Spectrum Sensing for Cognitive Radios Over Time-Frequency Doubly Selective Fading Channels. IEEE Transactions on Signal Processing, 63(2)
- Zhao C, Sun M, Li B, Zhao L & Peng X. (2014). Blind spectrum sensing for cognitive radio over time-variant multipath flat-fading channels. EURASIP Journal on Wireless Communications and Networking, 2014(1)
- Sun M, Li B, Song Q, Zhao L & Zhao C. (2014). Joint detection scheme for spectrum sensing over time‐variant flat fading channels. IET Communications, 8(12)
- Li B, Zhao C, Sun M, Zhou Z & Nallanathan A. (2014). Spectrum Sensing for Cognitive Radios in Time-Variant Flat-Fading Channels: A Joint Estimation Approach. IEEE Transactions on Communications, 62(8)
- Sun MW, Zhao L, Xu QC, Li B & Zhao CL. (2014). New spectrum sensing method under time-variant flat fading channels. Tongxin Xuebao Journal on Communications, 35(7)
- Sun M, Song Q, Li B, Zhao L & Zhao C. (2013). Nonlinear estimation for 60GHz millimeter-wave radar system based on Bayesian particle filtering. EURASIP Journal on Wireless Communications and Networking, 2013(1)
Conference Papers
- Besson Z, Sun M, Petrunin I, Hill A & Johnson D. (2025). Machine Learning Enhanced Multi-Sensor Fusion for Air Traffic Surveillance
- Holt D, Guo W, Sun M, Panagiotakopoulos D & Warston H. (2024). Deep Learning for Radar Classification
- Wright JS, Sun M, Davies ME, Proudler IK & Hopgood JR. (2024). Implementation of AKKF-based Multi-Sensor Fusion Methods in Stone Soup
- Sun M, Hodgskin-Brown R, Davies ME, Proudler IK & Hopgood JR. (2023). Adaptive Kernel Kalman Filter for Magnetic Anomaly Detection-based Metallic Target Tracking
- Wright JS, Hopgood JR, Davies ME, Proudler IK & Sun M. (2023). Implementation of Adaptive Kernel Kalman Filter in Stone Soup
- Sun M, Davies ME, Hopgood JR & Proudler I. (2021). Adaptive Kernel Kalman Filter Multi-Sensor Fusion
- Sun M, Davies ME, Proudler I & Hopgood JR. (2021). Adaptive Kernel Kalman Filter
- Sun M, Davies ME, Hopgood JR & Proudler I. (2021). Adaptive Kernel Kalman Filter Multi-Sensor Fusion
- Sun M, Davies ME, Proudler I & Hopgood JR. (2020). A Gaussian Process based Method for Multiple Model Tracking
- Sun M, Ding Y & Goussetis G. (2020). Adaptive Mode Selection and Power Allocation for D2D Underlay Cellular Networks with Dynamic Fading Channel
- Sun M, Shi M, Zhao C & Li B. (2015). Spectrum sensing for radar communications with unknown noise variance and time-variant channel
Books
- Sun M, Tian T, Zhao C & Li B. (2016). Spectrum sensing for cognitive radio systems with unknown non-zero-mean noise In Signal and Information Processing, Networking and Computers. CRC Press.
- Sun M, Lai X, Peng X, Zhao C & Li B. (2015). Efficient Joint Spectrum Sensing Algorithm Under Time-Variant Flat Fading Channel In Lecture Notes in Electrical Engineering (322). Springer International Publishing.
- Sun M, Zhang Y, Zhao L, Li B & Zhao C. (2014). Joint Detection Algorithm for Spectrum Sensing Over Multipath Time-Variant Flat Fading Channels In Lecture Notes in Electrical Engineering (246 LNEE). Springer International Publishing.
- Sun M, Li B, Zhao C, Liu Y & Li Z. (2012). Nonlinear Estimation for Ultra-Wideband Radar Based on Bayesian Particle Filtering Detector In Lecture Notes in Electrical Engineering (202 LNEE). Springer New York.