ABSTRACT :

In this paper, the problem of joint multi-pitch and direction-of-arrival (DOA) estimation for multichannel harmonic sinusoidal signals is considered. A spatio-temporal matrix signal model for a uniform linear array is defined, and then the ESPRIT method based on subspace techniques that exploits the invariance property in the time domain is first used to estimate the multi pitch frequencies of multiple harmonic signals. Followed by the estimated pitch frequencies, the DOA estimations based on the ESPRIT method are also presented by using the shift invariance structure in the spatial domain. Compared to the existing state-of-the-art algorithms, the proposed method based on ESPRIT without 2-D searching is computationally more efficient but performs similarly. An asymptotic performance analysis of the DOA and pitch estimation of the proposed method are also presented. Finally, the effectiveness of the proposed method is illustrated on a synthetic signal as well as real-life recorded data.

EXISTING SYSTEM :

  THE problem of estimating the pitch of a periodic signal is a fundamental problem that has received considerable attention for many years due to its wide application in areas such as audio and speech coding, compression, enhancement and classification of music, and speech analysis [1]–[5]. Many methods for parameter estimation in both single-pitch and multi-pitch scenarios have been reported (see [6]–[8] for an overview of existing pitch estimation methods). Direction-of-arrival (DOA) estimation with an array of spatially separated sensors is another key research topic in the field signal processing [10], [11], which has been widely studied in the past decades. Its application areas include radar [12], sonar [13], radio astronomy [14], geophysics [15], and speech processing with a microphone array [16]. In recent years, the problem of joint estimation of pitch and DOA of audio and speech signals received by multiple sensors has been extensively discussed for both single-pitch and multi-pitch scenarios in the literature [17]–[36]. Some of the key examples of applications that could benefit from this includes teleconferencing, surveillance applications, hands-free communication, and hearing aids, and so on.

PROPOSED SYSTEM :

The rest of the paper is organized as follows. The problem formulation is firstly described in Section II. In Section III, the spatio-temporal data model for the single-pitch case is defined and the single-pitch and DOA estimation method based on the ESPRIT technique is given. Then, the generalization of the proposed method to the case of joint multi-pitch and DOA estimation is presented. This is followed by the development of a joint pitch and DOA estimation algorithm in the presence of multi-path propagation. Section IV summarizes the proposed methods, and the asymptotic performance analysis follows in the subsequent section. Finally, simulation results and real-world signal data tests are discussed to illustrate the effectiveness of the proposed method.

SYSTEM REQUIREMENTS
SOFTWARE REQUIREMENTS:
• Programming Language : Python
• Font End Technologies : TKInter/Web(HTML,CSS,JS)
• IDE : Jupyter/Spyder/VS Code
• Operating System : Windows 08/10

HARDWARE REQUIREMENTS:

 Processor : Core I3
 RAM Capacity : 2 GB
 Hard Disk : 250 GB
 Monitor : 15″ Color
 Mouse : 2 or 3 Button Mouse
 Key Board : Windows 08/10