Dr. Marcel L. Hernandez Profile

Dr. Marcel L. Hernandez

Scientist at Univ. of Liverpool

SPIE Involvement:

Author

Publications (14)

Proceedings Article | 8 June 2022 Presentation + Paper

Stone Soup open source framework for tracking and state estimation: enhancements and applications

Jordi Barr, Oliver Harrald, Steven Hiscocks, Nicola Perree, Henry Pritchett, Sebastien Vidal, James Wright, Peter Carniglia, Emily Hunter, David Kirkland, Divy Raval, Siyuan Zheng, Anne Young, Bhashyam Balaji, Simon Maskell, Marcel Hernandez, Lyudmil Vladimirov

Proceedings Volume 12122, 1212205 (2022) https://doi.org/10.1117/12.2618495

KEYWORDS: Sensors, Detection and tracking algorithms, Radar, Filtering (signal processing), Data modeling, Gaussian filters, Algorithm development, Electronic filtering, Linear filtering, Video

Read Abstract +

Proceedings Article | 21 September 2007 Paper

Adaptive horizon sensor resource management: validating the core concept

Marcel Hernandez

Proceedings Volume 6699, 66990V (2007) https://doi.org/10.1117/12.734664

KEYWORDS: Sensors, Unmanned aerial vehicles, Motion models, Radium, Control systems, Computer programming, Document management, Passive remote sensing, Sensor performance, Astatine

Read Abstract +

This paper documents initial work into the development of a novel framework for sensor resource management: the Adaptive Horizon Sensor Management Framework (AHSMF). The concept at the core of AHSMF is that the optimal length of the planning horizon is dependent on the accuracy with which one can predict actual future performance, which is itself dependent on the level of uncertainty in the system (e.g. target state uncertainty). In the simplest case, in which there is no uncertainty (e.g. the target state and behavior are precisely known), a Dynamic Programming approach allows the planning horizon to extend far into the future as it is known precisely what the long-term impact of actions will be. However, we argue that in highly uncertain environments, the planning horizon should remain relatively short as the implications of actions on medium (and longer) term performance are hard to quantify. The basis of this paper is to validate this concept. We present two examples. The first is a simple toy problem in which we must plan over two time steps. We show that one step-ahead planning can perform better than two step-ahead planning if (i): the future impact of actions is highly variable, and (ii): the system controller has only limited information that does not capture this variability. The second example considers the problem of tracking a highly manoeuvring target using unmanned air vehicles (UAVs) that perform passive sensing. In this case, even more complex mechanisms influence the optimal length of the planning horizon. Two step-ahead planning outperformed one step-ahead planning (in terms of tracking accuracy) in many scenarios. However, in the most difficult, challenging and uncertain problems, with just one UAV tracking a target that frequently manoeuvred, one step-ahead planning was shown to perform significantly better. Future work will aim to identify the exact mechanisms responsible for the sub-optimality of multi-step-ahead planning in this, and other, pertinent applications. This will then provide a framework for adjusting the planning horizon online, in order to avoid unnecessary over-planning and maximize performance.

Proceedings Article | 2 May 2007 Paper

Simulating and testing autonomous behaviour in multiple airborne sensor systems

Moira Smith, Marcel Hernandez, Matthew Cooper

Proceedings Volume 6561, 65610O (2007) https://doi.org/10.1117/12.719482

KEYWORDS: Sensors, Unmanned aerial vehicles, Motion models, Algorithm development, Detection and tracking algorithms, Computer simulations, Monte Carlo methods, Performance modeling, Electromagnetic simulation, Environmental sensing

Read Abstract +

Proceedings Article | 19 May 2006 Paper

Weiss-Weinstein lower bound for maneuvering target tracking

T. Sathyan, M. Hernandez, A. Sinha, T. Kirubarajan

Proceedings Volume 6236, 62360G (2006) https://doi.org/10.1117/12.667792

KEYWORDS: Motion models, Matrices, Process modeling, Sensors, Switching, Astatine, Switches, Computer engineering, Detection and tracking algorithms, Radar

Read Abstract +

Proceedings Article | 19 May 2006 Paper

Multitarget-multisensor management for decentralized sensor networks

R. Tharmarasa, T. Kirubarajan, A. Sinha, M. Hernandez

Proceedings Volume 6236, 62360W (2006) https://doi.org/10.1117/12.665793

KEYWORDS: Sensors, Fluorescence correlation spectroscopy, Surveillance, Detection and tracking algorithms, Sensor performance, Target detection, Time metrology, Computer simulations, Error analysis, Optimization (mathematics)

Read Abstract +

Proceedings Article | 15 September 2005 Paper

Performance analysis underwater hydrophone arrays in tracking maneuvering sea-surface targets

Marcel Hernandez, Nick Goddard

Proceedings Volume 5913, 591314 (2005) https://doi.org/10.1117/12.616720

KEYWORDS: Sensors, Motion models, Target detection, Data modeling, Submerged target detection, Motion measurement, Detection and tracking algorithms, Time metrology, Signal to noise ratio, Monte Carlo methods

Read Abstract +

In this paper, we assess the capability of underwater hydrophone (UH) arrays to locate and track manoeuvring targets. A UH array is a horizontal line array of omnidirectional pressure sensors that is deployed on the seabed. The measurements at each UH array are then affected by two idiosyncrasies, termed "source direction ambiguity" and "coning error". In this paper, the posterior Cramer-Rao lower bound(PCRLB) is used as the measure of system performance, providing a bound on the optimal achievable accuracy of target state estimation. We demonstrate the impact of the measurement idiosyncrasies on the PCRLB, with the bound shown to be greater (poorer performance) than when using standard bearings-only sensors. We also include clutter (i.e. we allow each measurement to be either target generated or a false positive), as well as both state-dependent measurement errors and a state-dependent probability of detection. Building on previous work, we show that the measurement origin uncertainty can again be expressed as an information reduction factor (IRF), with this IRF now shown to be a function of both the target range and orientation in relation to each UH array. We consider simulated scenarios that contain features characteristic of recent sea trials conducted by QinetiQ Ltd. The two key features of the trial scenarios is that we have very sparse prior knowledge, and each target has the potential to perform a series of manoeuvres. We use a recent PCRLB formulation for tracking manoeuvring targets that approximates the potentially multi-modal target distribution using a best-fitting Gaussian distribution. We present simulation results for multi-sensor scenarios, demonstrating that this is indeed a difficult tracking problem. Tracking is particularly difficult when the target crosses the line of the UH arrays, making triangulation difficult; and when the target is in the "end-fire" of at least one UH array. It is also difficult to detect and triangulate distant targets. Future work will investigate the tightness of the PCRLB when compared with the performance of state-of-the-art tracking algorithms.

Proceedings Article | 25 August 2004 Paper

PCRLB-based multisensor array management for multitarget tracking

Ratnasingham Tharmarasa, Thiagalingam Kirubarajan, Marcel Hernandez

Proceedings Volume 5428, (2004) https://doi.org/10.1117/12.541884

KEYWORDS: Sensors, Target detection, Surveillance, Active sensors, Detection and tracking algorithms, Error analysis, Lead, Particle filters, Computer simulations, Numerical integration

Read Abstract +

Proceedings Article | 25 August 2004 Paper

A fast-jet pursuer-evader game: how to track a difficult target

Paul Horridge, Marcel Hernandez

Proceedings Volume 5428, (2004) https://doi.org/10.1117/12.542009

KEYWORDS: Sensors, Target detection, Motion models, Sensor networks

Read Abstract +

Proceedings Article | 5 January 2004 Paper

Multistatic radar resource management

Paul Horridge, Marcel Hernandez

Proceedings Volume 5204, (2004) https://doi.org/10.1117/12.504526

KEYWORDS: Sensors, Receivers, Target detection, Doppler effect, Radar, Particles, Transmitters, Particle filters, Statistical analysis, Error analysis

Read Abstract +

Proceedings Article | 5 January 2004 Paper

Adaptive sensor placement for target tracking in the presence of uncertainties

Kumaradevan Punithakumar, Thiagalingam Kirubarajan, Marcel Hernandez

Proceedings Volume 5204, (2004) https://doi.org/10.1117/12.504872

KEYWORDS: Sensors, Error analysis, Target detection, Unattended ground sensors, Motion models, Unmanned aerial vehicles, Submerged target detection, Warfare, Monte Carlo methods, Complex systems

Read Abstract +

Proceedings Article | 5 January 2004 Paper

Dynamic multisensor resource management with increased sensor utility

Marcel Hernandez, Paul Horridge

Proceedings Volume 5204, (2004) https://doi.org/10.1117/12.504514

KEYWORDS: Sensors, Target detection, Error analysis, Detection and tracking algorithms, Particle filters, Diamond, Computer programming, Matrices, Particles, Computer simulations

Read Abstract +

Proceedings Article | 5 January 2004 Paper

Large-scale optimal sensor array management for target tracking

Ratnasingham Tharmarasa, Thiagalingam Kirubarajan, Marcel Hernandez

Proceedings Volume 5204, (2004) https://doi.org/10.1117/12.504873

KEYWORDS: Sensors, Detection and tracking algorithms, Active sensors, Unattended ground sensors, Sensor performance, Time metrology, Error analysis, Laser induced plasma spectroscopy, Computer simulations, Particle filters

Read Abstract +

Proceedings Article | 25 August 2003 Paper

Improved data fusion through intelligent sensor management

Moira Smith, Christopher Angell, Marcel Hernandez, William Oxford

Proceedings Volume 5096, (2003) https://doi.org/10.1117/12.486928

KEYWORDS: Sensors, Data fusion, Target detection, Intelligent sensors, Detection and tracking algorithms, Research management, Roads, Sensor fusion, Raster graphics, Distributed computing

Read Abstract +

Proceedings Article | 7 August 2002 Paper

Efficient multisensor resource management using Cramer-Rao lower bounds

Marcel Hernandez, Thiagalingam Kirubarajan, Yaakov Bar-Shalom

Proceedings Volume 4728, (2002) https://doi.org/10.1117/12.478520

KEYWORDS: Sensors, Error analysis, Detection and tracking algorithms, Particle filters, Process control, Target detection, Monte Carlo methods, Submerged target modeling, Matrices, Warfare

Read Abstract +

Showing 5 of 14 publications

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Keywords/Phrases

Search In:

Publication Years