# The way multi-channel detection and estimation of the number of spatially-correlated radiation sources and the device for its implementation

(57) Abstract:

The invention relates to electrical engineering and can be used for detection and estimation of the number of spatially-correlated radiation sources in RDF, radar, sonar, geophysical and other multi-channel systems, passive and active locations that use antenna arrays. Achievable technical result is to increase the accuracy of determining the number of spatially-correlated radiation sources and the reliability of detection for eigenvalues of sample correlation matrices of the signals from the outputs of the N sensors of the antenna array. The aim is achieved in that the N - M last eigenvalues of the sample correlation matrix serves on extrapolator find evaluation "noise" components for M first eigenvalues and before the comparison with the thresholds of the M first eigenvalues subtract assessment "noise" components, and the thresholds for M the first eigenvalues are obtained by multiplying the normalized thresholds on the average noise power in the channel, which is calculated by extraprise functions. 1 C.p. f-crystals, 1 Il. The invention classifies the sources of radiation in RDF, radar, sonar, geophysical and other multi-channel systems, passive and active locations that use antenna arrays.A known way of estimating the number of spatially-correlated radiation sources [1], in which the signals of the radiation sources take the sensors of the antenna array, compute the sample correlation matrix (ACM) signals from the sensors of the antenna array, compute the eigenvalues (Sz) VKM and arrange them in descending order according to the obtained values of Sz VKM form information criterion Akaike (ICA) [1]:< / BR>

where m is a parameter of the criterion Akaike (m=1,.., N-1);

N is the number of sensors of the antenna array;

_{n}- eigenvalue VKM;

n is the number NW VKM (n = 1,..., N).The number of radiation sources M is determined by the minimum value of the criterion (1).The disadvantage of Akaike is the lack of accuracy of determining the number of radiation sources M [1, S. 446] and the lack of reliability of detection.The closest set of features of the present invention is a method of estimating the number of spatially-correlated radiation sources [2] , when katareena lattice, calculate Sz VKM. The procedure for estimating the number of spatially-correlated radiation sources is considered as a step-by-step process on the n-th step which compares the n-th Sz threshold. If Sz is more threshold then decide that the number of radiation sources is greater than n-1, and is compared with a threshold following NW. Otherwise, the process stops and decides that the number of radiation sources is n-1 [2].The threshold value for the first Sz calculated using the distribution function of the first Sz VKM [2] matrix of dimension N. the Threshold values for the second and subsequent Sz VKM calculated using the inequality, giving some estimate of the distribution function of the (M+1)-th NW matrix of dimension N, the distribution function of the first Sz matrix of dimension (N-M):

F

_{1}(N-M)F

_{M+1}(N), (2)

where F

_{1}(N - M) - distribution function of the first Sz VKM matrix of dimension (N-M);

F

_{M+1}(, + N) is the distribution function of (M+1)-th NW VKM matrix of dimension nThe disadvantage of this method is the lack of accuracy of determining the number of radiation sources and the lack of reliability of detection.For agoonline detection and estimation of the number of spatially-correlated radiation sources. Its essence consists in the following:

1. Receive signals from the N sensors of the antenna array, calculate MCV, calculate Sz VKM Marshal NW VKM in descending order.2. M NW first ACM served on subtractive device (N-M) last NW VKM served on the device extrapolation and to provide estimates of "noise" components for M NW first. On extraprise functions calculate an average noise power in the channel

3. Multiply the normalized values of the threshold on the resulting value of the average noise power in the channel is subtracted from the first M Sz

_{n}appropriate assessment "noise" components and compare the obtained values with the thresholds.4. If all thresholds are exceeded, then decide that the number of sources is equal to M and the procedure of assessment done.For a more accurate assessment of the number of radiation sources the proposed method is used in the form of step-by-step procedures. In the first step extrapolation doing one last noise Sz when M=N-1. If the thresholds for the first Sz M not exceeded, then the extrapolation procedure performed on the last two noise Sz when M=N-2, and so on until M=1. If the threshold is not exceeded when M=1, then a decision is made about the absence of radiation sources is the number of spatially-correlated radiation sources, shown in the drawing.In the inventive device, the extrapolation is performed using exponential functions of the form

< / BR>

where the constant;

L - the number of time samples used in the calculation of MCV;

k is a parameter which is calculated from the condition of minimization of the error

< / BR>

After finding the value of k is calculated "noise" components for M NW first by the formula (3) when n = 1,..., MThe average noise power in the channel is calculated as the average extraprise functions for all N eigenvalues

< / BR>

Thresholds for M the first eigenvalues are obtained by multiplying the normalized thresholds on the average power of noise in the channels (5). From M the first Sz

_{n}deducted the appropriate assessment "noise" components and the obtained values are compared with the thresholds.The normalized threshold values are calculated for a single average power of noise in the channels. Are used for calculation of multivariate normal distribution function Sz VKM:

< / BR>

where fluctuational component of the n-th NW VKM;

- average fluctuational component;

_{n}- dispersion fluctuational component.The inventive method multichannel detection and estimation of the number of spatially-correlated sources of radiation increases the accuracy of determining the number of radiation sources and increases the reliability of detection.Sources of information

1. Marple.-ml S. L., Digital spectral analysis and its applications: TRANS. from English. M.: Mir, 1990.2. Ermolaev Century. So, Radyushkin K. C. distribution Function of the maximum eigenvalue of the sample correlation matrix self-noise of the elements of the antenna array. "Izv. Higher education institutions. Radiophysics.- 1999.- So 42.- N 5.- C. 494-500. 1. The way multi-channel detection and estimation of the number of spatially-correlated sources of radiation, in which the signals spatially Cotonou lattice, calculate the sample correlation matrix of the above-mentioned signals, calculate your own values

_{n}the sample correlation matrix, ordered referred to their own values

_{n}in descending order, compare them with the threshold values, wherein before comparison with the threshold values of the M first mentioned eigenvalues

_{n}where M = N -1, N - 2, ... up to N - M = 1, subtract the appropriate assessment of noise components mentioned eigenvalues

_{n}that calculated by extrapolation (N - M) the last-mentioned eigenvalues

_{n}thresholds for M first mentioned eigenvalues

_{n}obtained by multiplying the normalized thresholds on the average noise power in the channel, which is calculated as the average value extraprise functions for all N mentioned eigenvalues

_{n}if all thresholds are exceeded obtained values then decide that the number of detected spatial-correlated radiation sources is equal to M, if the threshold is not exceeded when M = 1, then decide about the lack of spatially correlated sources emitted by the first value of

_{n'}use the exponential function of the form

< / BR>

- constant

L - the number of time samples used in the calculation of sample correlation matrix of the above-mentioned signals,

k is a parameter, which is calculated from the condition of minimization of the error , according to the criterion of least squares (N-M) of the last mentioned eigenvalues

_{n}< / BR>

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