Cramér-Rao Lower Bound for DOA Estimation with an Array of Directional Microphones in Reverberant Environments

In sound source localization, there is a fundamental size limit; the smaller the size, the smaller the directional cues that are relied on to pinpoint the sound source. As such, it is challenging to develop miniature sound source localization robotic system where space is too confined to employ conventional microphone arrays without compromising localization performance. Our previous studies show that through mechanical coupling with well-tuned structural parameters, directional microphones inspired by the parasitic fly Ormia ochracea can amplify the minute interaural time delay (ITD) by more than ten times, which enables the reduction of device size significantly while maintaining localization performance. In this paper, Cramer Rao lower bound (CRLB) is derived for the fly-ear inspired sensor and the conventional directional microphones to study the effects of mechanical coupling on the decrease of the theoretical lower bound of azimuth estimation. This improvement gives mobile robots the capability to reactively localize sound in an indoor environment. Using this miniature sensor, new sound source localization method is proposed to localize a stationary sound source in 2-D (azimuth and elevation). In the proposed sound localization method, Model-Free Gradient Descent (MFGD) optimization method, one of the main challenges is to choose the appropriate cost function to achieve minimum number of iterations and the smallest absolute error. To this end, different cost functions are proposed and investigated with different control schemes. Simulation results showed the ability of this technique to solve the ambiguity problem and localize the sound source.

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Multi-Source DOA Estimation in Reverberant Environments by Jointing Detection and Modeling of Time-Frequency Points

IEEE/ACM Transactions on Audio Speech and Language Processing ◽

10.1109/taslp.2020.3042705 ◽

2021 ◽

Vol 29 ◽

pp. 379-392

Author(s):

Maoshen Jia ◽

Yuxuan Wu ◽

Changchun Bao ◽

Christian Ritz

Keyword(s):

Doa Estimation ◽

Time Frequency ◽

Reverberant Environments

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Multi-source DOA estimation in reverberant environments using potential single-source points enhancement

Applied Acoustics ◽

10.1016/j.apacoust.2020.107782 ◽

2021 ◽

Vol 174 ◽

pp. 107782

Author(s):

Maoshen Jia ◽

Yitian Jia ◽

Shang Gao ◽

Jing Wang ◽

Shusen Wang

Keyword(s):

Doa Estimation ◽

Single Source ◽

Reverberant Environments ◽

Single Source Points

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Frequency Diverse Array MIMO Radar Adaptive Beamforming with Range-Dependent Interference Suppression in Target Localization

International Journal of Antennas and Propagation ◽

10.1155/2015/358582 ◽

2015 ◽

Vol 2015 ◽

pp. 1-10 ◽

Cited By ~ 6

Author(s):

Kuandong Gao ◽

Huaizong Shao ◽

Jingye Cai ◽

Hui Chen ◽

Wen-Qin Wang

Keyword(s):

Lower Bound ◽

Phased Array ◽

Interference Suppression ◽

Doa Estimation ◽

Mimo Radar ◽

Adaptive Beamforming ◽

Target Localization ◽

Equal Angle ◽

Multiple Input ◽

Frequency Diverse Array

Conventional multiple-input and multiple-output (MIMO) radar is a flexible technique which enjoys the advantages of phased-array radar without sacrificing its main advantages. However, due to its range-independent directivity, MIMO radar cannot mitigate nondesirable range-dependent interferences. In this paper, we propose a range-dependent interference suppression approach via frequency diverse array (FDA) MIMO radar, which offers a beamforming-based solution to suppress range-dependent interferences and thus yields much better DOA estimation performance than conventional MIMO radar. More importantly, the interferences located at the same angle but different ranges can be effectively suppressed by the range-dependent beamforming, which cannot be achieved by conventional MIMO radar. The beamforming performance as compared to conventional MIMO radar is examined by analyzing the signal-to-interference-plus-noise ratio (SINR). The Cramér-Rao lower bound (CRLB) is also derived. Numerical results show that the proposed method can efficiently suppress range-dependent interferences and identify range-dependent targets. It is particularly useful in suppressing the undesired strong interferences with equal angle of the desired targets.

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