Passive Geometry Calibration for Microphone Arrays Based on Distributed Damped Newton Optimization

Hu, De; Chen, Zhe; Yin, Fuliang

doi:10.1109/taslp.2020.3037532

Cited by 10 publications

(7 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Analyzing the numerical results from Table 1 , it can be observed that approaches such as in [ 28 ] do not take into account the compensation for the onset time, and do not achieve reasonably low position and orientation errors, regardless of the room reverberation time level. In the case of the moderate reverberation time (

[ms]), the other two methods [ 20 , 31 ] and the approach proposed in this article achieve very comparable results. In the case of a long reverberation time, the methods presented in [ 20 , 31 ] again perform comparably, while the algorithm proposed in this article achieves significantly better results for all evaluation metrics.…”

Section: Experimental Evaluationmentioning

confidence: 93%

“…To fully evaluate the performance of the proposed approach in practical deployments, we present the results of two additional experiments that do not take into account this mitigation, in which reverberant microphone signals are used for DoA estimation too. In the following two experiments, we compare the proposed method with several well-established state-of-the-art approaches [ 20 , 28 , 31 ]. To this end, we introduce three additional evaluation metrics that show the average displacement of the estimated positions from the ground-truth values.…”

Section: Experimental Evaluationmentioning

confidence: 99%

“…Recently, a method was proposed for splitting the cost function into multiple local cost functions, each assigned to a different node. Following this, distributed array calibration using the so-called damped Newtonian optimization was proposed in [ 20 ]. Another approach [ 21 ] consists of combining two types of objective functions, for orientation and time offset, respectively, with the aim of simultaneously estimating both these parameters in a distributed self-calibration and synchronization problem.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Reverberation-Robust Self-Calibration and Synchronization of Distributed Microphone Arrays by Mitigating Heteroscedasticity and Outlier Occurrence in TDoA Measurements

Woźniak,

Kowalczyk

2023

Sensors

View full text Add to dashboard Cite

The network of distributed microphone arrays is usually established in an ad hoc manner; hence, network parameters such as the mutual positioning and rotation of the arrays, positions of sources, and synchronization of their recording onset times are initially unknown. In this article, we consider the problem of passively jointly self-calibrating and synchronizing distributed arrays in reverberant rooms. We use a typical two-step approach where, initially, the relative geometry of the network is estimated using Direction of Arrival (DoA) measurements. Subsequently, the absolute scale and synchronization parameters are estimated using Time Difference of Arrival (TDoA) measurements. This article presents methods to improve the robustness and accuracy of estimation of the absolute geometric scaling and synchronization parameters in reverberant conditions, in which TDoA measurements do not follow a normal distribution; furthermore, outliers often occur. To remedy these issues, we propose a Weighted Least Squares (WLS) estimator and schema for weighting the TDoA measurements to increase the estimation accuracy from heteroscedastic TDoA measurements. In addition, we propose an iterative reweighing algorithm with a binary weight to detect and reject TDoA outliers, which exploits the residuals of the parametric model in the least absolute value minimization. A numerical evaluation shows significant improvements in the proposed method over the state of the art in terms of the relative scaling error and mean absolute value of the synchronization parameters.

show abstract

Section: Experimental Evaluationmentioning

confidence: 93%

Section: Experimental Evaluationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Reverberation-Robust Self-Calibration and Synchronization of Distributed Microphone Arrays by Mitigating Heteroscedasticity and Outlier Occurrence in TDoA Measurements

Woźniak,

Kowalczyk

2023

Sensors

View full text Add to dashboard Cite

show abstract

“…where l 0 is the frame shift of the correlation in (12), the SRO ε im between nodes i and m can either be estimated by the ACD approach [24] with…”

Section: Existing Sampling Rate Calibration Approachesmentioning

confidence: 99%

“…However, as sampling time increases, the natural phase relationships among node output signals are destroyed severely, which in turn affects the spatial information acquisition by using microphone networks. Consequently, this will significantly degrade the performance of many audio processing tasks [12]- [16]. Therefore, sampling rate synchronization is crucial for distributed acoustic sensor networks.…”

Section: Introductionmentioning

confidence: 99%

Distributed Sampling Rate Offset Estimation Over Acoustic Sensor Networks Based on Asynchronous Network Newton Optimization

Zhang

Bao

et al. 2023

IEEE/ACM Trans. Audio Speech Lang. Process.

Self Cite

View full text Add to dashboard Cite

Sampling rate synchronization is an inevitable issue in distributed acoustic sensor networks. In this paper, an analytical sampling rate offset (SRO) estimation approach is first proposed, and then, it is extended to a distributed method that suitable for acoustic sensor networks with arbitrary communication graphs. Specifically, a linear-phase drift model in the short-time Fourier transform domain is used to approximate the SRO between each pair of microphone nodes. Next, after unwrapping the temporally averaged phase information, SROs are recovered analytically via a new weighted-sum criterion. Based on this, a distributed cost function is established at each node to obtain the SROs of all nodes simultaneously in a distributed manner. Finally, a state-of-the-art distributed algorithm named asynchronous network Newton optimization is adopted to carry out the distributed SRO estimation. The proposed method can effectively estimate the SROs among acoustic sensor nodes in noisy and reverberant environments. Compared with the existing approaches, it does not require an external central processor, and only local communications among nodes are needed. Experimental results confirm the validity of the proposed method.

show abstract

A geometric solution to microphone array position calibration and its confidence interval analysis

Zhao,

Wang,

2024

Applied Acoustics

View full text Add to dashboard Cite

Passive Geometry Calibration for Microphone Arrays Based on Distributed Damped Newton Optimization

Cited by 10 publications

References 26 publications

Reverberation-Robust Self-Calibration and Synchronization of Distributed Microphone Arrays by Mitigating Heteroscedasticity and Outlier Occurrence in TDoA Measurements

Reverberation-Robust Self-Calibration and Synchronization of Distributed Microphone Arrays by Mitigating Heteroscedasticity and Outlier Occurrence in TDoA Measurements

Distributed Sampling Rate Offset Estimation Over Acoustic Sensor Networks Based on Asynchronous Network Newton Optimization

A geometric solution to microphone array position calibration and its confidence interval analysis

Contact Info

Product

Resources

About