his.sePublications
Change search
Link to record
Permanent link

Direct link
BETA
Johansson, Fredrik
Publications (10 of 16) Show all publications
Johansson, F. & Falkman, G. (2011). Real-time Allocation of Firing Units To Hostile Targets. Journal of Advances in Information Fusion, 6(2), 187-199
Open this publication in new window or tab >>Real-time Allocation of Firing Units To Hostile Targets
2011 (English)In: Journal of Advances in Information Fusion, ISSN 1557-6418, Vol. 6, no 2, p. 187-199Article in journal (Refereed) Published
Abstract [en]

The protection of defended assets such as military bases and population centers against hostile targets (e.g., aircrafts, missiles, and rockets) is a highly relevant problem in the military conflicts of today and tomorrow. In order to neutralize threats of this kind, they have to be detected and engaged before causing any damage to the defended assets. We review algorithms for solving the resource allocation problem in real-time, and empirically investigate their performance using the open source testbed SWARD. The reults show that many of the tested algorithms produce high quality solutions for small-scale problems. A novel vaiant of particle swarm optimization seeded with an enhanced greedy algorithm is described and is shown to perform best for large instances of the real-time allocation problem.

Place, publisher, year, edition, pages
ISIF, International Society of Information Fusion, 2011
National Category
Computer Sciences
Research subject
Technology
Identifiers
urn:nbn:se:his:diva-6299 (URN)
Available from: 2012-08-20 Created: 2012-08-20 Last updated: 2018-01-12Bibliographically approved
Johansson, F. & Falkman, G. (2010). A Suite of Metaheuristic Algorithms for Static Weapon-Target Allocation. In: Hamid R. Arabnia, Ray R. Hashemi, Ashu M. G. Solo (Ed.), GEM 2010: Proceedings of the 2010 International Conference on Genetic and Evolutionary Methods. Paper presented at 2010 International Conference on Genetic and Evolutionary Methods, GEM 2010, July 12-15, 2010, Las Vegas Nevada, USA (pp. 132-138). CSREA Press
Open this publication in new window or tab >>A Suite of Metaheuristic Algorithms for Static Weapon-Target Allocation
2010 (English)In: GEM 2010: Proceedings of the 2010 International Conference on Genetic and Evolutionary Methods / [ed] Hamid R. Arabnia, Ray R. Hashemi, Ashu M. G. Solo, CSREA Press, 2010, p. 132-138Conference paper, Published paper (Refereed)
Abstract [en]

The problem of allocating defensive weapon resources to hostile targets is an optimization problem of high military relevance. The need for obtaining the solutions in real-time is often overlooked in existing literature. Moreover, there  does not exist much research aimed at comparing the performance of different  algorithms for weapon-target allocation. We have implemented a suite of  metaheuristic algorithms for solving the static weapon-target allocation problem, and compare their real-time performance on a large set of problem instances using the open source testbed SWARD. The compared metaheuristic algorithms are ant colony optimization, genetic algorithms, and particle swarm optimization. Additionally, we have compared the quality of the generated allocations to those generated by a well-known maximum marginal return algorithm. The results show that the metaheuristic algorithms perform well on small- and medium-scale problem sizes, but that real-time requirements limit their usefulness for large search spaces.

Place, publisher, year, edition, pages
CSREA Press, 2010
Keywords
Combinatorial optimization, metaheuristics, real-time, resource allocation
National Category
Computer and Information Sciences
Research subject
Technology
Identifiers
urn:nbn:se:his:diva-4647 (URN)1-60132-145-7 (ISBN)
Conference
2010 International Conference on Genetic and Evolutionary Methods, GEM 2010, July 12-15, 2010, Las Vegas Nevada, USA
Available from: 2011-01-26 Created: 2011-01-26 Last updated: 2018-01-12Bibliographically approved
Johansson, F. (2010). Evaluating the Performance of TEWA Systems. (Doctoral dissertation). Örebro: Örebro University
Open this publication in new window or tab >>Evaluating the Performance of TEWA Systems
2010 (English)Doctoral thesis, monograph (Other academic)
Abstract [en]

It is in military engagements the task of the air defense to protect valuable assets such as air bases from being destroyed by hostile aircrafts and missiles. In order to fulfill this mission, the defenders are equipped with sensors and firing units. To infer whether a target is hostile and threatening or not is far from a trivial task. This is dealt with in a threat evaluation process, in which the targets are ranked based upon their estimated level of threat posed to the defended assets. Once the degree of threat has been estimated, the problem of weapon allocation comes into the picture. Given that a number of threatening targets have been identified, the defenders need to decide on whether any firing units shall be allocated to the targets, and if so, which firing unit to engage which target. To complicate matters, the outcomes of such engagements are usually stochastic. Moreover, there are often tight time constraints on how fast the threat evaluation and weapon allocation processes need to be executed. There are already today a large number of threat evaluation and weapon allocation (TEWA) systems in use, i.e. decision support systems aiding military decision makers with the threat evaluation and weapon allocation processes. However, despite the critical role of such systems, it is not clear how to evaluate the performance of the systems and their algorithms. Hence, the work in thesis is focused on the development and evaluation of TEWA systems, and the algorithms for threat evaluation and weapon allocation being part of such systems. A number of algorithms for threat evaluation and static weapon allocation are suggested and implemented, and testbeds for facilitating the evaluation of these are developed. Experimental results show that the use of particle swarm optimization is suitable for real-time target-based weapon allocation in situations involving up to approximately ten targets and ten firing units, while it for larger problem sizes gives better results to make use of an enhanced greedy maximum marginal return algorithm, or a genetic algorithm seeded with the solution returned by the greedy algorithm.

Place, publisher, year, edition, pages
Örebro: Örebro University, 2010. p. 177
Series
Örebro Studies in Technology, ISSN 1650-8580 ; 40
Keywords
air defense, information fusion, performance evaluation, threat evaluation, TEWA, weapon allocation
National Category
Computer and Information Sciences
Research subject
Technology
Identifiers
urn:nbn:se:his:diva-4695 (URN)978-91-7668-761-1 (ISBN)
Available from: 2011-02-15 Created: 2011-02-01 Last updated: 2018-01-12Bibliographically approved
Johansson, F. & Falkman, G. (2010). Real-time Allocation of Defensive Resources to Rockets, Artillery, and Mortars. In: FUSION 2010: 13th international Conference on Information Fusion, 26-29 July 2010, EICC, Edinburgh, UK. Paper presented at 13th international Conference on Information Fusion, 26-29 July 2010, EICC, Edinburgh, UK (pp. Article number 5712026). IEEE conference proceedings
Open this publication in new window or tab >>Real-time Allocation of Defensive Resources to Rockets, Artillery, and Mortars
2010 (English)In: FUSION 2010: 13th international Conference on Information Fusion, 26-29 July 2010, EICC, Edinburgh, UK, IEEE conference proceedings, 2010, p. Article number 5712026-Conference paper, Published paper (Refereed)
Abstract [en]

The protection of defended assets such as military bases and population centers against ballistic weapons (e.g. rockets and mortars) is a highly relevant problem in the military conflicts of today and tomorrow. In order to neutralize threats of this kind, they have to be detected and engaged before causing any damage to the defended assets. We propose algorithms for solving the resource allocation problem in real-time, and empirically investigate their performance using the open source testbed SWARD. The results show that a particle swarm optimization algorithm produce high quality solution for small-scale problems, and that agenetic algorithm yields the best solutions for the largest tested problem instances.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2010
Keywords
Air defense, resource management, weapon allocation
National Category
Computer and Information Sciences
Research subject
Technology
Identifiers
urn:nbn:se:his:diva-4645 (URN)2-s2.0-79952387876 (Scopus ID)978-0-9824438-1-1 (ISBN)
Conference
13th international Conference on Information Fusion, 26-29 July 2010, EICC, Edinburgh, UK
Available from: 2011-01-26 Created: 2011-01-26 Last updated: 2018-01-12Bibliographically approved
Johansson, F. & Falkman, G. (2010). SWARD: System for Weapon Allocation Research & Development. In: FUSION 2010: 13th international Conference on Information Fusion, 26-29 July 2010, EICC, Edinburgh, UK. Paper presented at 13th international Conference on Information Fusion, 26-29 July 2010, EICC, Edinburgh, UK (pp. Article number 5712067). IEEE conference proceedings
Open this publication in new window or tab >>SWARD: System for Weapon Allocation Research & Development
2010 (English)In: FUSION 2010: 13th international Conference on Information Fusion, 26-29 July 2010, EICC, Edinburgh, UK, IEEE conference proceedings, 2010, p. Article number 5712067-Conference paper, Published paper (Refereed)
Abstract [en]

The allocation of firing units to hostile targets is an important process within the air defense domain. Many algorithms have been proposed for solving various weapon allocation problems, but evaluation of the performance of such algorithms is problematic, since it does not exist any standard scenarios on which to test the algorithms. It is to a large extent unknown how weapon allocation algorithms compare to each other when it comes to solution quality. We have developed the testbed SWARD, making it possible to systematically compare algorithm performance, and to support the development of new weapon allocation algorithms.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2010
Keywords
Air defense, performance evaluation, testbed, weapon allocation
National Category
Computer and Information Sciences
Research subject
Technology
Identifiers
urn:nbn:se:his:diva-4646 (URN)2-s2.0-79952373970 (Scopus ID)978-0-9824438-1-1 (ISBN)
Conference
13th international Conference on Information Fusion, 26-29 July 2010, EICC, Edinburgh, UK
Available from: 2011-01-26 Created: 2011-01-26 Last updated: 2018-01-12Bibliographically approved
Johansson, F. & Falkman, G. (2009). A testbed based on survivability for comparing threat evaluation algorithms. In: John F Koegel Buford (Ed.), Intelligent Sensing, Situation Management, Impact Assessment, and Cyber-Sensing: Proceedings of SPIE Defense, Security, and Sensing 2009 -- Volume 7352. Paper presented at Intelligent sensing, situation management, impact assessment, and cyber-sensing : 15-17 April 2009, Orlando, Florida, United States (pp. Article ID 73520C). SPIE
Open this publication in new window or tab >>A testbed based on survivability for comparing threat evaluation algorithms
2009 (English)In: Intelligent Sensing, Situation Management, Impact Assessment, and Cyber-Sensing: Proceedings of SPIE Defense, Security, and Sensing 2009 -- Volume 7352 / [ed] John F Koegel Buford, SPIE , 2009, p. Article ID 73520C-Conference paper, Published paper (Refereed)
Abstract [en]

Threat evaluation is the process in which threat values are assigned to detected targets, based upon the inferred capabilities and intents of the targets to inflict damage to blue force defended assets. This is a high-level information fusion process of high importance, since the calculated threat values are used as input when blue force weapon systems are allocated to the incoming targets, a process often referred to as weapon allocation. Threat values can be calculated from a number of different parameters, such as the position of the closest point of approach (CPA) with respect to blue force defended assets, time required to reach the CPA, the target's velocity, and its type. A number of algorithms for calculating threat values have been suggested throughout literature, however, criteria to evaluate the performance of such algorithms seem to be lacking. In this paper, we discuss different ways to assess the performance of threat evaluation algorithms. In specific, we describe an implemented testbed in which threat evaluation algorithms can be compared to each other, based on a survivability criterion. Survivability is measured by running the threat evaluation algorithms on simulated scenarios and using the resulting threat values as input to a weapon allocation module. Depending on how well the threat evaluation is performed, the ability of the blue force weapon systems to eliminate the incoming targets will vary (and thereby also the survivability of the defended assets). Our obtained results for two different threat evaluation algorithms are presented and analyzed.

Place, publisher, year, edition, pages
SPIE, 2009
Series
Proceedings of SPIE--the International Society for Optical Engineering ; v. 7352.
Keywords
air defense, TEWA, threat evaluation, weapon allocation. weapon assignment
National Category
Computer and Information Sciences
Research subject
Technology
Identifiers
urn:nbn:se:his:diva-3222 (URN)10.1117/12.816819 (DOI)2-s2.0-69849106220 (Scopus ID)9780819476180 (ISBN)
Conference
Intelligent sensing, situation management, impact assessment, and cyber-sensing : 15-17 April 2009, Orlando, Florida, United States
Available from: 2009-06-26 Created: 2009-06-26 Last updated: 2018-01-13Bibliographically approved
Johansson, F. & Falkman, G. (2009). An empirical investigation of the static weapon-target allocation problem. In: Ronnie Johansson, Joeri van Laere and Jonas Mellin (Ed.), Proceedings of the 3rd Skövde Workshop on Information Fusion Topics (SWIFT 2009): . Paper presented at Proceedings of the 3rd Skövde Workshop on Information Fusion Topics (SWIFT 2009), 12-13 Oct 2009, Skövde, Sweden (pp. 63-67). University of Skövde
Open this publication in new window or tab >>An empirical investigation of the static weapon-target allocation problem
2009 (English)In: Proceedings of the 3rd Skövde Workshop on Information Fusion Topics (SWIFT 2009) / [ed] Ronnie Johansson, Joeri van Laere and Jonas Mellin, University of Skövde , 2009, p. 63-67Conference paper, Published paper (Refereed)
Abstract [en]

The allocation of weapons to targets (such as missiles and hostile aircrafts) is a well-known resource allocation problem within the field of operations research. It has been proven that this problem, in general, is NP-complete. For this reason, optimal solutions to the static weapon-target allocation (WTA) problem can not be obtained in real-time for large-scale problems. We try to find the limit for how large problems that can be solved optimally in real-time by exhaustive search algorithms through running empirical experiments. We also propose a heuristic genetic algorithm for solving larger-scale problems.

Place, publisher, year, edition, pages
University of Skövde, 2009
Series
Skövde University Studies in Informatics, ISSN 1653-2325 ; 2009:3
National Category
Computer and Information Sciences
Research subject
Technology
Identifiers
urn:nbn:se:his:diva-3547 (URN)978-91-978513-2-9 (ISBN)
Conference
Proceedings of the 3rd Skövde Workshop on Information Fusion Topics (SWIFT 2009), 12-13 Oct 2009, Skövde, Sweden
Available from: 2010-01-07 Created: 2010-01-07 Last updated: 2018-01-12Bibliographically approved
Johansson, F. & Falkman, G. (2009). Performance Evaluation of TEWA Systems for Improved Decision Support. In: Vicenç Torra, Yasuo Narukawa, Masahiro Inuiguchi (Ed.), Proceedings of the 6th International Conference on Modeling Decisions for Artificial Intelligence (MDAI 2009): . Paper presented at Modeling Decisions for Artificial Intelligence: 6th International Conference, MDAI 2009, Awaji Island, Japan, November 30–December 2, 2009 (pp. 205-216). Springer Berlin/Heidelberg
Open this publication in new window or tab >>Performance Evaluation of TEWA Systems for Improved Decision Support
2009 (English)In: Proceedings of the 6th International Conference on Modeling Decisions for Artificial Intelligence (MDAI 2009) / [ed] Vicenç Torra, Yasuo Narukawa, Masahiro Inuiguchi, Springer Berlin/Heidelberg, 2009, p. 205-216Conference paper, Published paper (Refereed)
Abstract [en]

In air defense situations, decision makers have to protect defended assets through assigning available firing units to threatening targets in real-time. To their help they have decision support systems known as threat evaluation and weapon allocation (TEWA) systems. The problem of performance evaluation of such systems is of great importance, due to their critical role. Despite this, research on this problem is close to non-existing. We are discussing the use of survivability and resource usage cost as comparative performance metrics, which can be used for comparing the effectiveness of different system configurations, by using simulations. These metrics have been implemented into a testbed, in which we have performed some comparative experiments. Our results show that changes of individual parts of the threat evaluation and weapon allocation system configuration can have a large effect on the effectiveness of the system as a whole, and illustrate how the metrics and the testbed can be used.

 

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2009
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 5861 LNAI
Keywords
Performance evaluation, testbed, TEWA, threat evaluation, weapon allocation
National Category
Computer and Information Sciences
Research subject
Technology
Identifiers
urn:nbn:se:his:diva-3537 (URN)10.1007/978-3-642-04820-3_19 (DOI)000276970400019 ()2-s2.0-84886568234 (Scopus ID)978-3-642-04819-7 (ISBN)978-3-642-04820-3 (ISBN)
Conference
Modeling Decisions for Artificial Intelligence: 6th International Conference, MDAI 2009, Awaji Island, Japan, November 30–December 2, 2009
Available from: 2010-01-07 Created: 2010-01-07 Last updated: 2018-01-12Bibliographically approved
Johansson, F. & Falkman, G. (2008). A Bayesian network approach to threat evaluation with application to an air defense scenario. In: Proceedings of the 11th International Conference on Information Fusion, FUSION 2008, Cologne, 30 June 2008–3 July 2008: . Paper presented at 11th International Conference on Information Fusion, FUSION 2008; Cologne; Germany; 30 June 2008 through 3 July 2008 (pp. 1352-1358). IEEE Computer Society
Open this publication in new window or tab >>A Bayesian network approach to threat evaluation with application to an air defense scenario
2008 (English)In: Proceedings of the 11th International Conference on Information Fusion, FUSION 2008, Cologne, 30 June 2008–3 July 2008, IEEE Computer Society, 2008, p. 1352-1358Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, a precise description of the threat evaluation process is presented. This is followed by a review describing which parameters that have been suggested for threat evaluation in an air surveillance context throughout the literature, together with an overview of different algorithms for threat evaluation. Grounded in the findings from the literature review, a threat evaluation system have been developed. The system is based on a Bayesian network approach, making it possible to handle imperfect observations. The structure of the Bayesian network is described in detail. Finally, an analysis of the system’s performance as applied to a synthetic scenario is presented.

Place, publisher, year, edition, pages
IEEE Computer Society, 2008
Keywords
Bayesian networks, TEWA, threat assessment, threat evaluation, weapons allocation, weapons assignment
National Category
Computer Sciences
Research subject
Technology
Identifiers
urn:nbn:se:his:diva-3611 (URN)10.1109/ICIF.2008.4632368 (DOI)2-s2.0-56749125106 (Scopus ID)978-3-00-024883-2 (ISBN)978-3-8007-3092-6 (ISBN)
Conference
11th International Conference on Information Fusion, FUSION 2008; Cologne; Germany; 30 June 2008 through 3 July 2008
Available from: 2010-01-29 Created: 2010-01-29 Last updated: 2018-01-12Bibliographically approved
Johansson, F. & Falkman, G. (2008). A Comparison between Two Approaches to Threat Evaluation in an Air Defense Scenario. In: Modeling Decisions for Artificial Intelligence: 5th International Conference, MDAI 2008 Sabadell, Spain, October 30-31, 2008. Proceedings. Paper presented at 5th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2008; Sabadell; Spain; 30 October 2008 through 31 October 2008 (pp. 110-121). Springer Berlin/Heidelberg
Open this publication in new window or tab >>A Comparison between Two Approaches to Threat Evaluation in an Air Defense Scenario
2008 (English)In: Modeling Decisions for Artificial Intelligence: 5th International Conference, MDAI 2008 Sabadell, Spain, October 30-31, 2008. Proceedings, Springer Berlin/Heidelberg, 2008, p. 110-121Conference paper, Published paper (Refereed)
Abstract [en]

 Threat evaluation is a high-level information fusion problem of high importance within the military domain. This task is the foundation for weapons allocation, where assignment of blue force (own) weapon systems to red force (enemy) targets is performed. In this paper, we compare two fundamentally different approaches to threat evaluation: Bayesian networks and fuzzy inference rules. We conclude that there are pros and cons with both types of approaches, and that a hybrid of the two approaches seems both promising and viable for future research.

 

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2008
Series
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN 0302-9743 ; 5285
Keywords
Bayesian networks, fuzzy inference rules, fuzzy logic, threat assessment, threat evaluation, weapons allocation
National Category
Computer Sciences
Research subject
Technology
Identifiers
urn:nbn:se:his:diva-2419 (URN)10.1007/978-3-540-88269-5_11 (DOI)000261348700011 ()2-s2.0-58049107646 (Scopus ID)978-3-540-88268-8 (ISBN)978-3-540-88269-5 (ISBN)
Conference
5th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2008; Sabadell; Spain; 30 October 2008 through 31 October 2008
Available from: 2008-12-03 Created: 2008-12-03 Last updated: 2018-01-13Bibliographically approved
Organisations

Search in DiVA

Show all publications