Students

Conor Benson Wins Best Session Presentation at AMOS

Anonymous — Mon, 10 Oct 2022 16:41:58 +0000

Conor Benson Wins Best Session Presentation at AMOS Anonymous (not verified) Mon, 10/10/2022 - 10:41

Simulation and Analysis of Event Camera Data for Non-Resolved Objects

Non-Resolved Object Characterization

Photon counters and exposure-based cameras cannot simultaneously provide exquisite temporal and spatial resolution in one sensor. Event (i.e. neuromorphic) cameras provide both and promise to advance studies of high-speed temporal and spatial intensity variations. Potential space domain awareness (SDA) applications include streak-based orbit determination and high frequency light curve analysis. No dynamic event camera simulations for non-resolved objects have been conducted. In this work, we develop an event camera model for this purpose. Referencing the event camera literature, we approximate the event pixel dynamics as a first order differential equation driven by logarithmic photon flux. The photon arrivals are modeled as a stochastic Poisson process. Considering static point sources with constant and time-varying mean brightness as well as moving sources, we use this model to explore event data dependencies on various target and sensor parameters. These parameters include the target’s mean brightness, on-sky motion rate, the brightness amplitude and frequency as well as the event threshold and event circuit parameters. For the time-varying brightness case, we also study how frequency estimate signal-to-noise depends on these parameters. We then validate simulation results against real event data of non-resolved space objects, showing clear consistencies. The observed sensitivity to target parameters demonstrates the great potential of event cameras for high spatio-temporal resolution astrometry and photometry. Finally, we conduct frequency analysis on the real data.

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Sam Fedeler presents at International Astronautical Congress (IAC)

Anonymous — Tue, 20 Sep 2022 22:33:23 +0000

Sam Fedeler presents at International Astronautical Congress (IAC) Anonymous (not verified) Tue, 09/20/2022 - 16:33

Paris, France 2022

For a variety of mission-critical objectives in Space Domain Awareness (SDA), it is relevant to maintain estimates over large regions of state space using highly non-Gaussian distributions. This problem is broadly applicable in initial orbit determination, maneuver detection, and collision avoidance, and observing targets in this context often necessitates search over the feasible region. Often, this search process results in a large set of null detections. This paper explores methodologies for utilizing negative information in this context, with a special focus on the well-known admissible region. Given a Gaussian mixture representation of the admissible region, a novel methodology for splitting mixands in an arbitrary measurement space is presented. A mixand weight update is derived for the key scenario in which no detection is made at a measurement epoch. Merging methodologies are applied, and the resultant Gaussian sum filter is demonstrated for a representative case in which follow-on tracking of a geostationary object is desired.

https://www.iafastro.org/events/iac/iac-2022/

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Sam Wishnek and Sam Fedeler at SciTech!

Anonymous — Fri, 10 Jan 2020 16:40:51 +0000

Sam Wishnek and Sam Fedeler at SciTech! Anonymous (not verified) Fri, 01/10/2020 - 09:40

Sam Wishnek (right) and Sam Fedeler (left) presented their work at AIAA SciTech this week!

Sam W.'s work focused on accurately calibrating ultra-wide field of view cameras for Space Domain Awareness applications as well as information-optimal photometrically varying streak extraction.
Astrometry and Time-Resolved Photometry From Streaks Using Calibrated Ultra-Wide Field of View Cameras.

Sam F.'s work is related to optimal tasking of Space Domain Awareness sensors to track collections of space objects, minimizing overal covariance measures
Monte Carlo Tree Search Methods for Telescope Tasking.

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A successful PhD defense for Julian Brew!

Anonymous — Tue, 29 Oct 2019 18:59:59 +0000

A successful PhD defense for Julian Brew! Anonymous (not verified) Tue, 10/29/2019 - 12:59

Please join me in congratulating Dr. Julian Brew for successfully defending his PhD dissertation on October 28!

While this post is a little late, it's better late than never! His dissertation is titled Using Sample-Based Continuation Techniques to Efficiently Compute Subspace Reachable Sets and Pareto Surfaces.

Congratulations Dr. Brew!

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Sam Fedeler receives Draper & NSF Fellowships!

Anonymous — Fri, 12 Apr 2019 14:50:53 +0000

Sam Fedeler receives Draper & NSF Fellowships! Anonymous (not verified) Fri, 04/12/2019 - 08:50

Please join me in congratulating graduate student Samuel Fedeler, who has been selected for both the prestigious Draper Fellowship Program and the National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP)! Either of these programs are highly competitive with selection rates in the neighborhood of 10%. Being selected for both is a rare accomplishment!

An article about this award is posted on the Smead AES Department website.

Again, congratulations!

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A Sequential Dempster Shafer Particle Filter

Anonymous — Wed, 19 Sep 2018 12:03:57 +0000

A Sequential Dempster Shafer Particle Filter Anonymous (not verified) Wed, 09/19/2018 - 06:03

I'm pleased to say that Johnny Worthy's work on extending Dempster Shafer evidential reasoning to sequential particle filters has been accepted as a journal article in IEEE Transactions on Aerospace and Electronic Systems. The paper, titled "Sequential Estimation from Uninformative Priors Using Dempster-Shafer Theory," has particular value when initiating sequential estimation processes with unobservable priors.

In the paper, he rigorously constructs belief mass functions used to update both the belief and plausibility of individual particle hypotheses. Using Dempster's rule of combination, the collective belief and plausibility 'surfaces' can be constructed. Interestingly, he is able to show that as the problem becomes observable, the belief and plausibility surfaces collapse on to one another and exactly match a Bayesian particle filter at that instant. A final advantage of the approach is that belief may be assigned to the hypothesis that the true state does not lie within the admissible region, thus letting the operator know if their admissible region assumptions are incorrect.

Dr. Worthy was able to validate the approach on real data from the GT-SORT telescope using observations of the tumbling COSMOS 1247 space object.

Please join me in congratulating Johnny on this accomplishment!

A link to the published paper will be added when the paper is posted onine.

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