Efficient binaural rendering of spherical microphone array data by linear filtering

High-quality rendering of spatial sound fields in real-time is becoming increasingly important with the steadily growing interest in virtual and augmented reality technologies. Typically, a spherical microphone array (SMA) is used to capture a spatial sound field. The captured sound field can be reproduced over headphones in real-time using binaural rendering, virtually placing a single listener in the sound field. Common methods for binaural rendering first spatially encode the sound field by transforming it to the spherical harmonics domain and then decode the sound field binaurally by combining it with head-related transfer functions (HRTFs). However, these rendering methods are computationally demanding, especially for high-order SMAs, and require implementing quite sophisticated real-time signal processing. This paper presents a computationally more efficient method for real-time binaural rendering of SMA signals by linear filtering. The proposed method allows representing any common rendering chain as a set of precomputed finite impulse response filters, which are then applied to the SMA signals in real-time using fast convolution to produce the binaural signals. Results of the technical evaluation show that the presented approach is equivalent to conventional rendering methods while being computationally less demanding and easier to implement using any real-time convolution system. However, the lower computational complexity goes along with lower flexibility. On the one hand, encoding and decoding are no longer decoupled, and on the other hand, sound field transformations in the SH domain can no longer be performed. Consequently, in the proposed method, a filter set must be precomputed and stored for each possible head orientation of the listener, leading to higher memory requirements than the conventional methods. As such, the approach is particularly well suited for efficient real-time binaural rendering of SMA signals in a fixed setup where usually a limited range of head orientations is sufficient, such as live concert streaming or VR teleconferencing.

Identification of maneuvering objects during structural and system control of airspace

Работа посвящена построению процедуры идентификации маневрирующих объектов с использованием критерия идеального наблюдателя и фильтрации параметров трасс при сопровождении средствами мониторинга в интересах структурносистемного контроля воздушного пространства. Для минимизации среднеквадратических ошибок оценок координат и скоростей движения объектов разработаны алгоритмы экстраполяции параметров траекторий путем задания корректирующего шумового ускорения и замены результатов фильтрации оценок координат на измеренные значения при распознавании маневра. Обоснованы параметры фильтрации с шумовым ускорением в зависимости от точности измерений пространственных характеристик и идентификации при группировании однотипных признаков с наибольшими значениями условных вероятностей ситуаций отождествления объектов Purpose. This work addresses construction of the procedure for identifying maneuvering air objects in the process of tracking their routes. Monitoring tools during structural and system air space control are employed. The study is aimed to establish the abilities of correct identification of objects and false alarm at various standard errors of measurements of angular coordinates and to determine ways to increase efficiency of identifications performed due to selection of filtering options during trace tracking. Methodology. Identification of objects was performed according to the ideal observer criterion by comparing estimates of angular coordinates of objects subjected to linear filtering with corrective noise acceleration. In order to minimize root-mean-square errors of coordinates and motion velocity estimates of objects, route parameter extrapolation algorithms are obtained by setting correcting noise acceleration and replacing the results of filtering coordinate estimates with measured values during manoeuvre recognition. Due to a priori uncertainty of route parameters, target tracking was initially performed using recurring linear filtering while maintaining the priority of straight uniform movement. The recognition of the maneuver was carried out as a result of exceeding the difference between the measured and filtered values of the target coordinates of the threshold value. Findings. Filtering parameters with noise acceleration are justified depending on the accuracy of measurements of spatial characteristics and identification when grouping identification features with the highest values of conditional probabilities of situations for the objects under identification. As a result of replacing filtered parameters of alignments containing areas with rotations of 10 and 20, measured values for standard bearing errors (1 ... 2), the maximum error in determining directions for objects reaches 0.8 and 0.9, respectively. When replacing the estimates of the parameters of the alignments obtained using a recurring linear filter without taking into account noise acceleration, the coordinate values measured at the bearing error (0 . 5 ... 2), the errors of the filtered bearing of the targets at the angles of rotation of 10are (0 . 2 ... 1). When maneuvering objects with turns by 20, the largest value of the standard bearing error increases to 1.2. By increasing the accuracy of the diaper from 2 to 0.5, the probability of correct identification of objects in monitoring tools performing noise correction acceleration filtering increases by about 3 times and reaches a value of 0.9. As a result of replacing the estimates of the parameters of the alignments filtered taking into account the corrective noise acceleration with the results of measurements, the probability of correct identification of objects with standard bearing errors of not more than 0.5decreases from 0.9 to 0.85. Originality/value. The identification of maneuvering air objects is performed using filtering of route parameters calculated with the help of the ideal observer criterion. For the most efficient identification, the identification features belonging to the same object must be established according to the highest conditional probability of the identification situation. To minimize errors in estimation of the angular coordinates of objects, a procedure for filtering motion parameters with corrective noise acceleration is implemented

8 Point DIT-FFT Algorithm Using Verilog

The importance of Digital Signal method (DSP) algorithms has increased drastically in recent times, the two very important techniques of DSP unit the Distinct Fourier rework (DFT) and thus the fast Fourier rework (FFT). DFT is mostly utilized within the applications sort of convolution, a linear filtering etc. Another algorithmic rule to reason DFT efficiently is that the fast Fourier remodels (FFT). Fast Fourier rework processor incorporates a vital role inside the sphere of communication system like audio broadcasting and digital video etc.

Robust Filtering of Sequences with Periodically Stationary Multiplicative Seasonal Increments

We consider stochastic sequences with periodically stationary generalized multiple increments of fractional order which combines cyclostationary, multi-seasonal, integrated and fractionally integrated patterns. We solve the filtering problem for linear functionals constructed from unobserved values of a stochastic sequence of this type based on observations of the sequence with a periodically stationary noise sequence. For sequences with known matrices of spectral densities, we obtain formulas for calculating values of the mean square errors and the spectral characteristics of the optimal filtering of the functionals. Formulas that determine the least favourable spectral densities and the minimax (robust) spectral characteristics of the optimal linear filtering of the functionals are proposed in the case where spectral densities of the sequence are not exactly known while some sets of admissible spectral densities are given.

Ground Photometric Measurements Inversion Methods for Space Object Characteristics Based on Nonlinear Filtering: A Short Review

: The ground space optical observation system considered as one of the main measurement methods to observe space object in Medium Earth Orbit (MEO), Highly Elliptical Orbit (HEO), and Geostationary Orbit (GEO) experiences difficulties in forming high-solution images for objects located in GEO that only appear as several light spots with limited pixels due to the impacts of observing distance, resolution ratio, and other atmospheric conditions. The light curve is the time duration of an object’s observed brightness. Through light curves, right ascension, and declination of space objects obtained from the ground-based optical observation system, the characteristic of space objects such as position, velocity, size, shape, and material can be inverted. This paper has analyzed the principles, applications, merits, and demerits of several non-linear filtering methods in detail. Besides, the scientific description of inversion for characteristics of a non-resolved space object from ground photometric measurements and the essence of the non-linear filtering inversion method have also been clarified. A selection principle of the non-linear filtering inversion method for different space object characteristics is then proposed, and the developing direction of such inversion methods is also described in the end.

Widely Linear Filtering for Multi-Impairment Compensation in Coherent Optical Systems

We propose a blind joint equalization algorithm for M-QAM signals based on a widely linear filtering approach. The proposed scheme jointly compensates receiver IQ imbalance and polarization mixing, along with carrier recovery, followed by transmitter IQ imbalance compensation. We first investigate the proposed scheme's tolerance to transceiver IQ Imbalance, polarization mixing, phase noise and frequency offset through numerical simulations for 32 GBd PM-16QAM and PM-64QAM signals and compare its performance with the conventional digital processing algorithms. Further, with the proposed algorithm, we experimentally demonstrate the improvement in Q² value to up to ~ 1.22 dB for a 32 GBd PM-16QAM and ~ 3.72 dB for a 16 GBd PM-64QAM signal with a phase imbalance of 9^o. We show that the MSE convergence of the proposed joint equalizer is much faster than conventional DSP algorithms. Deployment of such an equalizer in optical communication systems is beneficial due to its improved tolerance to multiple impairments, albeit with increased complexity.

Widely Linear Filtering for Multi-Impairment Compensation in Coherent Optical Systems

We propose a blind joint equalization algorithm for M-QAM signals based on a widely linear filtering approach. The proposed scheme jointly compensates receiver IQ imbalance and polarization mixing, along with carrier recovery, followed by transmitter IQ imbalance compensation. We first investigate the proposed scheme's tolerance to transceiver IQ Imbalance, polarization mixing, phase noise and frequency offset through numerical simulations for 32 GBd PM-16QAM and PM-64QAM signals and compare its performance with the conventional digital processing algorithms. Further, with the proposed algorithm, we experimentally demonstrate the improvement in Q² value to up to ~ 1.22 dB for a 32 GBd PM-16QAM and ~ 3.72 dB for a 16 GBd PM-64QAM signal with a phase imbalance of 9^o. We show that the MSE convergence of the proposed joint equalizer is much faster than conventional DSP algorithms. Deployment of such an equalizer in optical communication systems is beneficial due to its improved tolerance to multiple impairments, albeit with increased complexity.