264 citations · 728 across the 7 of their papers we have counts for
7 papers
Second Order Statistics Analysis and Comparison between Arithmetic and Geometric Average Fusion
Tiancheng Li, Hongqi Fan, Jesús G. Herrero +1
Two fundamental approaches to information averaging are based on linear and logarithmic combination, yielding the arithmetic average (AA) and geometric average (GA) of the fusing i…
Partial Consensus and Conservative Fusion of Gaussian Mixtures for Distributed PHD Fusion
Tiancheng Li, Juan M Corchado, Shudong Sun
We propose a novel consensus notion, called "partial consensus", for distributed GM-PHD (Gaussian mixture probability hypothesis density) fusion based on a peer-to-peer (P2P) senso…
Joint Smoothing, Tracking, and Forecasting Based on Continuous-Time Target Trajectory Fitting
Tiancheng Li, Huimin Chen, Shudong Sun +1
We present a continuous time state estimation framework that unifies traditionally individual tasks of smoothing, tracking, and forecasting (STF), for a class of targets subject to…
The Optimal Arbitrary-Proportional Finite-Set-Partitioning
Tiancheng Li
This paper considers the arbitrary-proportional finite-set-partitioning problem which involves partitioning a finite set into multiple subsets with respect to arbitrary nonnegative…
Do we always need a filter?
Tiancheng Li, Juan M. Corchado, Javier Bajo +2
Since the groundbreaking work of the Kalman filter in the 1960s, considerable effort has been devoted to various discrete time filters for dynamic state estimation, especially incl…
Fighting Sample Degeneracy and Impoverishment in Particle Filters: A Review of Intelligent Approaches
Tiancheng Li, Shudong Sun, Tariq P. Sattar +1
During the last two decades there has been a growing interest in Particle Filtering (PF). However, PF suffers from two long-standing problems that are referred to as sample degener…
Numerical Fitting-based Likelihood Calculation to Speed up the Particle Filter
Tiancheng Li, Shudong Sun, Juan M. Corchado +2
The likelihood calculation of a vast number of particles is the computational bottleneck for the particle filter in applications where the observation information is rich. For fast…