Nonlinear Filtering With Sample-Based Approximation Under Constrained Communication: Progress, Insights and Trends
W Song, Z Wang, Z Li, J Wang… - IEEE/CAA Journal of …, 2024 - ieeexplore.ieee.org
The nonlinear filtering problem has enduringly been an active research topic in both
academia and industry due to its ever-growing theoretical importance and practical …
academia and industry due to its ever-growing theoretical importance and practical …
Target detection using quantized cloud MIMO radar measurements
Target detection is studied for a cloud multiple-input multiple-output (MIMO) radar using
quantized measurements. According to the local sensor quantization strategies and fusion …
quantized measurements. According to the local sensor quantization strategies and fusion …
Distributed Radar Multi-frame Detection with Local Censored Observations
J Lu, S Zhou, X Peng, A Wang - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Distributed radar multiframe detection (DR-MFD) provides an efficient approach for detecting
dim targets. However, the transmission and processing of a large number of measurements …
dim targets. However, the transmission and processing of a large number of measurements …
Design of optimal non-uniform quantizer in imperfect noisy reporting channels for collaborative spectrum sensing
M Naderipour, A Taherpour… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
We design an optimal non-uniform quantizer for collaborative spectrum sensing (CSS) in
cognitive radio networks (CRNs). We assume non-ideal reporting channels are and consist …
cognitive radio networks (CRNs). We assume non-ideal reporting channels are and consist …
Model-Driven Deep Learning for Distributed Detection with Binary Quantization
Within the realm of rapidly advancing wireless sensor networks (WSNs), distributed
detection assumes a significant role in various practical applications. However, critical …
detection assumes a significant role in various practical applications. However, critical …
Model-Driven Deep Learning for Distributed Detection in WSNs with Binary Quantization
Within the realm of rapidly advancing wireless sensor networks (WSNs), distributed
detection assumes a significant role in various practical applications. However, critical …
detection assumes a significant role in various practical applications. However, critical …
Scalable multilevel quantization for distributed detection
A scalable algorithm is derived for multilevel quantization of sensor observations in
distributed sensor networks, which consist of a number of sensors transmitting a summary …
distributed sensor networks, which consist of a number of sensors transmitting a summary …
Fast multilevel quantization for distributed detection based on Gaussian approximation
An iterative algorithm is derived for multilevel quantization of sensor observations in
distributed sensor networks, where each sensor transmits a summary of its observation to …
distributed sensor networks, where each sensor transmits a summary of its observation to …
Maximum average entropy-based quantization of local observations for distributed detection
MA Wahdan, MA Altınkaya - Digital Signal Processing, 2022 - Elsevier
In a wireless sensor network, multilevel quantization is necessary to find a compromise
between minimizing the power consumption of sensors and maximizing the detection …
between minimizing the power consumption of sensors and maximizing the detection …
Multi-static sonar distributed quantized detection fusion method based on NP criterion
D Zhang, L Gao, T Teng - 2018 OCEANS-MTS/IEEE Kobe …, 2018 - ieeexplore.ieee.org
Multi-static sonar fusion detection system has advantages over the mono-static sonar
system, such as the large-scale surveillance over the sea. In this paper, the method of …
system, such as the large-scale surveillance over the sea. In this paper, the method of …