An example of scenario-based evaluation of military capability areas An impact assessment of alternative systems on operations

Suojanen, Marko; Kuikka, Vesa; Nikkarila, Juha-Pekka; Nurmi, Jari

doi:10.1109/syscon.2015.7116817

Cited by 7 publications

(2 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In recent years, small UAVs have improved greatly, e.g., increased range, speed, and payload capacity [9]. The dualuse capabilities of small UAVs [10] enable them to be utilized by various actors for different purposes. Defense forces can leverage the use of small UAVs to gain strategic advantage over their enemies by conducting surveillance and reconnaissance missions and launching strikes over the enemies [11], [12].…”

Section: Introductionmentioning

confidence: 99%

Enhancing TDE-based Drone DoA Estimation with Genetic Algorithms and Zero Cyclic Sum

Fernandes,

Apolinário Júnior,

Seixas

2023

Anais Do XVI Congresso Brasileiro De Inteligência Computacional

View full text Add to dashboard Cite

This paper discusses a way to enhance an acousticbased approach to obtaining the direction of arrival (DoA) of a drones ego noise using a microphone array. We focus on obtaining better time delay estimations (TDE) from a set of possible candidates. Recently, a large number of works have been put forward to detect and classify drones with different techniques. However, more investigation is required to tackle the drone DoA estimation problem using the time difference of arrival between pairs of microphones for the case of strongly corrupted audio signals, possibly by noise and multipath. The main problem in a complex acoustic environment is accurately estimating the time difference of arrival. With a traditional approach, this task becomes nearly impossible without the line of sight assumption, that is, whenever the highest cross-correlation peak between signals does not correspond to the delay between them. This paper uses genetic algorithms to search for the correct delays between pairs of microphones among a set of possible delays (primary and secondary delays). We define a fitness function based on the concept of zero cyclic sum of closed loops, i.e., when forming a closed loop, the sum of all theoretical delays should equal zero. A drawback of closed loops is that incorrect delays may result in a zero-sum; we thus created a fitness function that considers all possible closed loops of a given array. We exploited different approaches to estimate the direction of arrival using the combination of genetic algorithms and zero cyclic sum. In our experiments, the method successfully found all correct delays in simulations, providing strong evidence of its effectiveness when a correct delay exists among multiple possible delays. Furthermore, in experimental trials, it significantly enhanced the number of correct delays detected, further validating its utility and potential in practical scenarios.

show abstract

Section: Introductionmentioning

confidence: 99%

Enhancing TDE-based Drone DoA Estimation with Genetic Algorithms and Zero Cyclic Sum

Fernandes,

Apolinário Júnior,

Seixas

2023

Anais Do XVI Congresso Brasileiro De Inteligência Computacional

View full text Add to dashboard Cite

show abstract

“…Constant development of new applications for Unmanned Aerial Vehicles (UAV) attracts the attention of sectors such as law-enforcement [1], [2], agriculture [3], emergency services response [4], and the military [5]. This increasing interest can be attributed to its simplicity and cost-effectiveness.…”

Section: Introductionmentioning

confidence: 99%

Applying the majority voting rule in acoustic detection and classification of drones

Fernandes¹,

Apolinario²,

Ramos³

et al. 2021

Anais Do XXXIX Simpósio Brasileiro De Telecomunicações E Processamento De Sinais

View full text Add to dashboard Cite

This paper discusses an approach to target detection and classification based on acoustic signals collected using one single microphone. This study has applications to sonar or any other sound event classification system. We divide the problem into two parts, namely feature extraction and target detection and classification. We use an optimization step based on human auditory uncertainty. We employ a majority voting rule for every set of feature vectors, i.e., an estimate is only performed if the majority agrees. We conducted experiments using a single channel of the AIRA-UAS dataset, a public database of raw drone noises collected with an array of microphones mounted on a drone. This dataset comprises many different kinematics, with different spectra. The features we used are based on the Mel-Frequency Cepstral Coefficients (MFCC) and the Short-Time Fourier Transform of raw signals. We used the K-Nearest Neighbors algorithm for classification and adopted the crossvalidation strategy to evaluate the method. We observed that the use of MFCC results in less biased estimations, which favors the voting strategy. The detection in the proposed method reached a probability of false positive near 0%, even with a small set of votes, and a classification accuracy of 99.1%. These metrics satisfy the requirements of most civilian and military applications.

show abstract

Designing Military Command and Control Systems as System of Systems – An Analysis of Stakeholder Needs and Challenges

Lundberg,

Stirna,

Andersson

2024

Lecture Notes in Computer Science

View full text Add to dashboard Cite

An example of scenario-based evaluation of military capability areas An impact assessment of alternative systems on operations

Cited by 7 publications

References 8 publications

Enhancing TDE-based Drone DoA Estimation with Genetic Algorithms and Zero Cyclic Sum

Enhancing TDE-based Drone DoA Estimation with Genetic Algorithms and Zero Cyclic Sum

Applying the majority voting rule in acoustic detection and classification of drones

Designing Military Command and Control Systems as System of Systems – An Analysis of Stakeholder Needs and Challenges

Contact Info

Product

Resources

About