| 1. |
- khan, Imran, et al.
(författare)
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Remotely Controlled Laboratory Setup for Active Noise Control and Acoustic Experiments
- 2012
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Ingår i: 2012 9th International Conference on Remote Engineering and Virtual. - Bilbao : IEEE. - 9781467325424 - 9781467325400
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Konferensbidrag (refereegranskat)abstract
- This paper presents a remotely controlled educational experiments setup for Active Noise Control (ANC) and acoustic experiments. The experiments setup is based on the Virtual Instruments Systems in Reality (VISIR) open source platform, National Instruments LabVIEW software and a Digital Signal Processor TMS320C6713 from Texas Instruments. The software development and equipment are controlled remotely form a client PC using a standard web browser. The proposed laboratory setup focuses on ANC experiments applied to noise in a ventilation duct. The laboratory setup will enable students to test and investigate properties and behaviour of adaptive algorithms in reality as compared to more confined simulations usually carried out in Matlab etc. The general steps in ANC, such as the feasibility of active control, designing, testing and debugging ANC algorithms, configuration and implementation of an active control system, are all covered. In addition students will be able to study the effect of analog to digital converters (ADC), anti-aliasing filters, digital to analog converters (DAC) and reconstruction filters using digital signal processing in reality, etc. The laboratory setup is suitable for a wide range of courses such as sound related experiments in upper secondary school physics, digital signal processing, adaptive signal processing, and acoustics at university level.
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| 2. |
- Hameed, Khurram, et al.
(författare)
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Far-Field DOA Estimation of Uncorrelated RADAR Signals through Coprime Arrays in Low SNR Regime by Implementing Cuckoo Search Algorithm
- 2022
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Ingår i: Electronics. - : MDPI AG. - 2079-9292. ; 11:4
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Tidskriftsartikel (refereegranskat)abstract
- For the purpose of attaining a high degree of freedom (DOF) for the direction of arrival (DOA) estimations in radar technology, coprime sensor arrays (CSAs) are evaluated in this paper. In addition, the global and local minima of extremely non-linear functions are investigated, aiming to improve DOF. The optimization features of the cuckoo search (CS) algorithm are utilized for DOA estimation of far-field sources in a low signal-to-noise ratio (SNR) environment. The analytical approach of the proposed CSAs, CS and global and local minima in terms of cumulative distribution function (CDF), fitness function and SNR for DOA accuracy are presented. The parameters like root mean square error (RMSE) for frequency distribution, RMSE variability analysis, estimation accuracy, RMSE for CDF, robustness against snapshots and noise and RMSE for Monte Carlo simulation runs are explored for proposed model performance estimation. In conclusion, the proposed DOA estimation in radar technology through CS and CSA achievements are contrasted with existing tools such as particle swarm optimization (PSO).
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