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Daniel Frisch

Daniel Frisch

Wissenschaftlicher Mitarbeiter
Multilateration
Gruppe: FuseNetsGroup
Raum: CS
Tel.: +49 721 608-45249
daniel frischXyq5∂kit edu

Adenauerring 2

Gebäude 50.20

D-76131 Karlsruhe



Data Fusion in Networks Group

Our group is part of the Intelligent Sensor-Actuator-Systems (ISAS) Laboratory. We are interested in data fusion for networked multisensor systems including distributed and decentralized state estimation, Kalman filtering with event-based and asynchronous communication, and state estimation for large-scale systems.

 

 

In particular, we investigate:

Robust Kalman filtering

  • quantification of uncertainties
  • combination of stochastic and unknown but bounded noise models

Fusion under unknown dependencies

  • conservative bounds on unknown correlations
  • parameterization of dependencies in nonlinear estimation

Large-scale state estimation

  • estimation methods for spatially distributed systems
  • fusion of heterogeneous estimates

Estimation with communication constraints

  • event-based state estimation
  • filtering of quantized and asynchronous measurements

Multilateration for Tracking of Airplanes

MLAT_geo
Geometry with two aircraft and five sensors. Signal propagation times are proportional to the euclidean distance between aircraft and sensors.
MLAT_time
Timing diagram with two aircraft and five sensors, showing how the signal arrival times are formed.

Multilateration is a technique to estimate the position of a transmitter of propagating waves based on measurements taken from sensors at different distant positions. It is applied in radar, sonar, and radio astronomy, for example [TDOA_FKIE]. We set up the measurement equation that calculates the time of arrival (TOA) of the signal at a given sensor based on its distance to the source and the propagation velocity. When enough measurements are available, only one aircraft position can reproduce the encountered TOA. Sometimes we work with time differences of arrival (TDOA) which can be calculated via cross correlation of the sampled input signal. Current research at our institute covers multi target tracking [SPIE17_Hanebeck] and multi sensor data fusion [Fusion18_Radtke]. 

We estimate aircraft positions in datasets from our cooperation partner Frequentis Comsoft in Durlach. We develop advanced techniques to localize aircraft also in cases where it is problematic at present, like sensors with non-synchronized clocks, for example due to GPS breakdown, and when more than one aircraft send indistinguishable messages. 

At ISAS, we also apply multilateration to localize sound sources in experiments at the institute. With multiple directional sensors, we want to bridge multilateration and directional statistics [Fusion18_Li-SE2]. With new distributed information fusion algorithms, we want to merge measurements from multiple sensor nodes.
 

click here to watch the video MLAT_Sound_SS18.mp4

 

Contact: Daniel Frisch, Kailai LiBenjamin Noack 


Exercises
Titel Typ Semester Ort
Vorlesung (V) mit Übung (Ü) WS 18/19
Vorlesung (V) mit Übung (Ü) WS 17/18

Vorlesung: Raum -102, Gebäude 50.34
Übung: Raum SR 148, Gebäude 50.20



Seminars
Title Type Semester Person in Charge
Seminar WS 18/19 Daniel Mockenhaupt
Proseminar WS 18/19 Peter Christos Digas
Seminar SS 2018 Axel Trefzer
Seminar WS 17/18 Andre Langenstein
Proseminar WS 17/18 Stanislav Arnaudov


Completed Theses
Title Type Person in Charge
Bachelor thesis Stefano Miceli


Conference Presentations
Title Conference Authors Speaker Source

SDF 2018

Kailai Li, Daniel Frisch, Susanne Radtke, Benjamin Noack, and Uwe D. Hanebeck

Daniel Frisch

Paper



Siehe unsere zentrale Publikationsliste