Optimum placement of microphone array for sound capture using genetic algoritms

Birinci, Isil Yazgan
Leblebicioğlu, Mehmet Kemal
This paper presents a new method based on genetic algorithm for the optimum placement of microphone arrays for high-quality sound pickup. Microphone arrays are being used for the purposes of direction-of-arrival estimation and tracking of sound sources [1][2] as well as high quality sound capture by focusing on a source [3]. The placement of microphones has direct effect on the sound quality acquired [4][5]. The method proposed in this paper uses a metric function that takes this effect into account and optimizes this function for a signal source and several noise sources within a predefined two-dimensional region considering practical microphone placement constraints. With the employment of genetic algorithm on this problem, the method is easily applicable to any arbitrary region and the practical constraints on the placement of microphones are taken into account from the design level.
IEEE 14th Signal Processing and Communications Applications


Online state estimation for discrete nonlinear dynamic systems with nonlinear noise and interference
Demirbaş, Kerim (2015-01-01)
This paper presents a real-time recursive state filtering and prediction scheme (PR) for discrete nonlinear dynamic systems with nonlinear noise and random interference, such as undesired random jamming or clutter. The PR is based upon discrete noise approximation, state quantization, and a suboptimal implementation of multiple composite hypothesis testing. The PR outperforms both the sampling importance resampling (SIR) particle filter and auxiliary sampling importance resampling (ASIR) particle filter; wh...
Posterior Cram'er-Rao Lower Bounds for Extended Target Tracking with Random Matrices
Sarıtaş, Elif; Orguner, Umut (2016-07-08)
This paper presents posterior Cram'er-Rao lower bounds (PCRLB) for extended target tracking (ETT) when the extent states of the targets are represented with random matrices. PCRLB recursions are derived for kinematic and extent states taking complicated expectations involving Wishart and inverse Wishart distributions. For some analytically intractable expectations, Monte Carlo integration is used. The bounds for the semi-major and minor axes of the extent ellipsoid are obtained as well as those for the exte...
Tracking of multiple ground targets in clutter with interacting multiple model estimator
Korkmaz, Yusuf; Baykal, Buyurman; Department of Electrical and Electronics Engineering (2013)
In this thesis study, single target tracking algorithms including IMM-PDA and IMM-IPDA algorithms; Optimal approaches in multitarget tracking including IMM-JPDA, IMM-IJPDA and IMM-JIPDA algorithms and an example of Linear Multi-target approaches in multitarget tracking including IMM-LMIPDA algorithm have been studied and implemented in MATLAB for comparison. Simulations were carried out in various realistic test scenarios including single target tracking, tracking of multiple targets moving in convoy fashio...
Interacting multiple model probabilistic data association filter using random matrices for extended target tracking
Özpak, Ezgi; Orguner, Umut; Department of Electrical and Electronics Engineering (2018)
In this thesis, an Interacting Multiple Model – Probabilistic Data Association (IMM-PDA) filter for tracking extended targets using random matrices is proposed. Unlike the extended target trackers in the literature which use multiple alternative partitionings/clusterings of the set of measurements, the algorithm proposed here considers a single partitioning/clustering of the measurement data which makes it suitable for applications with low computational resources. When the IMM-PDA filter uses clustered mea...
Optimal Path Tracking Control of a Quadrotor UAV
Suicmez, Emre Can; Kutay, Ali Türker (2014-05-30)
This paper presents the linear quadratic tracking (LQT) control of a quadrotor UAV by solving discrete time matrix difference Riccati Equation. First, the nonlinear dynamic model of the quadrotor is obtained by using Newton's equations of motion. Then, the nonlinear dynamic model is linearized around hover condition. The linearized dynamic model is used to solve the optimal control problem. A trade off between good tracking performance and energy consumption is made while defining the performance index (cos...
Citation Formats
I. Y. Birinci and M. K. Leblebicioğlu, “Optimum placement of microphone array for sound capture using genetic algoritms,” presented at the IEEE 14th Signal Processing and Communications Applications, Antalya, TURKEY, 2006, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/39575.