The method of correlation investigation of acoustic signals with priority placement of microphones

Reasonable benefits of using multi-channel structure of digital correlation with high priority placement of one of the microphones for calculation autocorrelation. Peculiarities and effectiveness for application of CAD for designing of correlational back-end processors on the crystals of programmable logical integrated circuits have been determined.


I. INTRODUCTION
Development of theoretical foundations of information technology and software -hardware correlation signal processing is actual scientific -applied problem to be solved in many industries. Identification of sources of acoustic signals (SAS) relatively to spatial placement of microphones -receivers of acoustic signals (RAS) is also included.
An example of the use of acoustic signals is sound intelligence, which is a part and a type of artillery reconnaissance. Methods and devices used in sound intelligence allow to determine the coordinates of artillery and mortar batteries of the enemy by the sound of their shots and adjust their artillery fire defining the actual shells and mines hit by the sound of explosions.
The advantages of this type of intelligence are the independence of visibility conditions due to which exploration and maintenance of fire by sound are possible at night, in fog, in the smoke, weak dependence on terrain and local items, allowing exploration in of forest and cross country, and in the mountain as well, the ability to conduct hidden reconnaissance continuously for a long time.
Analysis of the known research results. An example of a successful but far from optimal solution of such problem is working out localization accumulated information systems by C. Birchflid and D. Hilmar. [4], [5], [6], [7]. The determination of spatial parameters ( ) azimuth and distance to the SAS ( ) the use of a certain number of ( q ) correlators for a given number of those ) (m microphones is taken as the base of the system.
The example of the structure of Acoustic Localization by Accumulated Correlation (ALAC) system is shown in [4] ( Fig. 1).  So, according to the information technology of the correlation processing of the SAS signals, proposed in [4], the required amount of ) (q correlators for a given number of the ) (m microphones is determined by the expression: The graph of dependency (2) with different numbers of microphones is shown in Fig.2.
For implementation of each correlator in ALAC system the integrated assessment multiplicative correlation function is used by the expression: , ( ( t x j integrating analog signals, essentially limiting its functionality, simplifying and increasing the speed and accuracy also prevents it implementation based on digital microelectronics crystals and programmable integrated-circuit logic (FPGA).
The purpose of the work is to develop and explore systemic and structural characteristics of digital special processor computing centered multiplicative correlation function.

II. MAIN PART
Formulation of the problem. In order to investigate the principles of improving and optimizing system features of digital correlators as the basic components of the discovering system, analysis of system features of special processor and computing digital multiplicative correlation estimates by the expression is performed [8]: where: register a digital value j which corresponds to the time delay t of the acoustic signal ) (t x between two microphones placed at different distance from SAS This correlation algorithm of digital processing acoustic signals on a base of multiplicative function (4) is greatly simplified if before the ADC pre-differentiation analog ) (t x signal is performed and it is passed through a device of automatic gain control, is shown in Fig. 4.

III. RESULTS OF THE INVESTIGATION
The basic structure of the investigated correlation processing of acoustic signals special processor designed for their processing is shown in Fig. 5.
The following notions are used in Fig.5:  For example, when the number of points of the correlation function m = 4096 binary code t has 12 bits, that corresponds to t 0.0025% measurement accuracy and uncertainty, and at m = 1024, corresponds to 10-bit binary code and the error does not exceed 0,001.

VI. CONCLUSION
The proposed method of optimizing the structure of multichannel digital correlator with priority spatial placement of a microphone and application module correlation function to process acoustic signals, can significantly simplify the algorithm of calculations, reduce the hardware complexity correlator which enhance its performance, justifying feasibility and effectiveness of these solutions in the established system of monitoring sources of acoustic signals and implementation of special processors in microelectronic implementation on crystals FPGA Altera Cyclone 3 with the Quartus 2.