Particle Filtering with Propagation Delayed Measurements

This paper investigates the problem of propagation delayed measurements in a particle filtering scenario. Based on implicit constraints specified by target dynamics and physics rules of signal propagation, authors apply the ideas that were first proposed in their previous work to the case of particle filters. Unlike the deterministic sampling based approach called propagation delayed measurement filter (PDMF) in their previous work, the new algorithm proposed here (called as PDM particle filter (PDM-PF)) has the potential to be used with general nonlinear models. This advantage and the estimation results of PDM-PF are illustrated in a challenging target tracking scenario by making comparisons to PDMF along with some other alternative particle filters.


Entropy Calculation in Particle Filters
Orguner, Umut (2009-04-11)
This paper presents a differential entropy calculation method to be used for particle mixtures in particle filters. First it is shown that the exact differential entropy of particle mixtures is minus infinity and therefore useless in practice. The disadvantage of using discrete entropy formulation instead of differential entropy is also explained. Unlike the kernel-based methods in the literature, a Bayes rule based approximation is then proposed. The performance of the algorithm is illustrated on a basic G...
Pseudo-Linear Kalman Filter for Attitude Estimation of a Spinning Nanosatellite
Söken, Halil Ersin; Kallio, Esa; Visala, Arto; Selkainaho, Jorma (null; 2017-06-09)
This paper presents the pseudo-linear estimation approach to the high-rate spinning small spacecraft attitude estimation problem. The sensor suit utilised in the presented approach uses gyro, magnetometer and sun-sensor measurements. The presented estimation technique has been designed particularly for the problem of attitude determination during the Aalto-1 nanosatellite's Plasma Brake Experiment (PBE). The design of the PBE demands the satellite to be spun up to 200 deg/s for deploying the tether by the u...
Ring based FIR-IIR best delay LS inverse filters
Aktas, M; Tuncer, Temel Engin (2004-04-30)
In this paper, we investigate the best delay LS inverse filter design problem. We propose FIR-IIR LS inverse filters to improve the LS error performance for the same complexity. Furthermore we present a new approach for the design of FIR-IIR LS inverse filters by using a special selection procedure for the IIR part. We derived the closed form LS error expressions and compared with the practical results in order to effectively show the performance improvement in this case. In general 4-5 dB improvement is ac...
Design of attitude estimation algorithms for inertial sensors only measurement scenarios
Candan, Batu; Söken, Halil Ersin; Department of Aerospace Engineering (2022-3-24)
This thesis proposes four novel robust Kalman filter algorithms for attitude estimation using only the measurements of an inertial measurement unit. Efficiency and optimality of the Kalman filter based attitude filters are correlated with appropriate tuning of the covariance matrices. Manual tuning process is a difficult and time-consuming task. Specifically, the inertial measurement unit-only attitude estimation filters are prone to the external accelerations unless their covariances are adapted to gain ro...
Delay and Peak-Age Violation Probability in Short-Packet Transmissions
Devassy, Rahul; Durisi, Giuseppe; Ferrante, Guido Carlo; Simeone, Osvaldo; Uysal, Elif (2018-06-22)
This paper investigates the distribution of delay and peak age of information in a communication system where packets, generated according to an independent and identically distributed Bernoulli process, are placed in a single-server queue with first-come first-served discipline and transmitted over an additive white Gaussian noise (AWGN) channel. When a packet is correctly decoded, the sender receives an instantaneous error-free positive acknowledgment, upon which it removes the packet from the buffer. In ...
Citation Formats
U. Orguner, “Particle Filtering with Propagation Delayed Measurements,” 2010, Accessed: 00, 2020. [Online]. Available: