# The way ovchinnikov data processing for detection of a radiation source

(57) Abstract:

The invention relates to measurement technology and automation. How is that for a more narrow global maximum detected radiation source perform the conversion of the first signal in the spectral Fourier transform and convert the second signal into a complex-conjugate spectral representation of the Fourier transform, obtaining mutual spectrum, obtaining an extended range of the spectrum by mutual alignment of the modules of the amplitudes of its harmonics at a constant, leaving unchanged the sum of squares of amplitudes of all modules harmonics, and then the inverse Fourier transform of the extended spectrum. Achievable technical result is to obtain a global maximum on the order of magnitude narrower than crosscorrelation functions, and thus reduce the level of side lobes. 4 Il. The invention relates to measurement technology and automation and can be used in the DFS, when processing signals from sensors sound, electromagnetic waves or streams of particles.The known device for processing signals that implement the correlation method (e.g., Celenia values of the correlation function. This processing method is optimal only in the class of linear processing of signals.Closest to the present invention is a method for detecting signals from a source of radiation by correlation processing. C. the USSR N 1472916 G 06 F 15/336, publ. 15.04.89), which includes the receipt of signals from the two sensors, converting them into a spectral representation, the multiplication of complex amplitudes of the harmonics of the two spectra and the complex mutual spectrum, which is subjected to inverse Fourier transform to calculate the values of the correlation function.The disadvantage of this method of treatment is that it is optimal only in the class of linear processing of signals (in some cases, the global maximum has a large width and high amplitude side lobes) and therefore needs to improve noise immunity (reliable determination of the presence of the source) and improve the accuracy of determining the position of the global maximum (for a precise estimation of the coordinates of the radiation source).Thus, the object of the invention is the creation of such a processing method, the Z which has a narrow global maximum with small lateral lobes and, as the result is of an unforgettable source.This objective is achieved in that when processing data for detecting the radiation source converts the first signal into a spectral representation of the Fourier and converting the second signal into a complex-conjugate spectral representation of the Fourier transform, obtaining mutual spectrum by multiplying the complex amplitudes of the harmonics of the obtained spectra of the first and second signals and a subsequent inverse Fourier transformation, it is proposed before the inverse Fourier transform to produce the expansion of mutual spectrum by aligning modules amplitudes of its harmonics at a constant, leaving unchanged the sum of squares of amplitudes of all modules harmonics.The essence of the method lies in the fact that take into account properties of complex mutual spectrum. The known properties of the spectral transform S tof(x)S() =

^{+}

_{-}f(x)e

^{-j}

^{x}dx.

If the function f

_{1}(x) and f

_{2}(x) differ only by a shift in the value of d for the variable x: f

_{2}(x) = f

_{1}(x-d), their integrated spectra differ only by the phase factor e

^{-j}

^{d}:S

_{1}() =

^{+}

_{-}f

_{1}(x)e

^{-j}

^{x}dx;

< / BR>

From these relations it can be seen, Spectr carries information about the distance. Information on the amount of shift d is obtained by finding the phase difference for each harmonic spectra of S

_{1}, S

_{2}. The phase difference for all harmonics can be obtained in the form of a phase component of the spectrum of S

_{in}(), which is obtained by multiplying S

_{1}on the complex conjugation of the spectrum S

_{2}:

S

_{in}() = S

_{1}()S

^{*}

_{2}(),

where * is a sign of complex conjugation. S

_{in}() is called mutual spectrum signals f

_{1}(x) and f

_{2}(x). Complex-conjugate spectrum S

^{*}

_{2}(a) is obtained by applying inverse Fourier transform to the function f

_{2}(x).Inverse Fourier transformation of S

_{in}() is the cross-correlation function of the signals f

_{1}(x) and f

_{2}(x), which is widely used in technical applications for determining the amount of shift d. The error of determination of the shift depends on the width of the global maximum and the presence and amplitude of side lobes, which are always present near this maximum. The width of the maximum depends on the width of the reciprocal of the spectrum, the narrow maximum is obtained with a uniform spectrum.The described method involves obtaining new spectrum S() by expanding mutual peoplebecause the offset d. The amplitude spectrum must be aligned to a constant so that the energy spectrum S() remained equal energy spectrum S

_{in}():

< / BR>

With technical implementations of this condition will hold if S() is a uniform spectrum, and the sum of the squares of modules of its harmonics is equal to the sum of the squares of the harmonic spectrum S

_{in}().

The method may be implemented by a device, the block diagram of which is shown in Fig. 1. The scheme includes a block 1 of the memory for storing samples of a one-dimensional signal f1, the memory unit 2 for storing a sample of the one-dimensional signal f2, unit 3 performing the direct Fourier transform unit 4 perform the inverse Fourier transform, the blocks 5 and 6 which is the memory for storing the results of operation of units 3 and 4, respectively (spectra S

_{1}() and S

^{*}

_{2}()), unit 7 calculate the reciprocal of the spectrum of S

_{in}() by multiplying S

_{in}() = S

_{1}()S

^{*}

_{2}(), the memory unit 8 for storing the reciprocal of the spectrum, block 9 expanding the range by aligning modules harmonics, unit 10 perform the inverse Fourier transform unit 11 to the memory storage of the processing zIf the input realization signals represent a sample from a two-dimensional aggregate (EmOC is Riez transforms, as a result, Z, is stored in the block 11, is a function of two shear arguments. The peak of the function Z correspond to two arguments - shifts "horizontal" and "vertical" coordinates.In Fig. 2 shows a diagram that implements the method for the case when one of the signals is known in advance. For example, if the active location of the transmitted signal is known, therefore, the unit 1 receives the sample signal reflected by the target and in blocks 2, 4 there is no need, as data on paired spectrum of the emitted signal can be pre-stored in the memory unit 6.An example implementation of a method for detecting seismic sources of sound vibrations is shown in Fig. 3. It is assumed that the direction finding is performed by three sensors that are not located on one straight line. Sampling data from sensors placed in the memory blocks 1, 2, 14, blocks 3, 3', 3" perform a direct Fourier transform, 4, 4', 4" perform the inverse transform, 5, 5', 5" store direct spectra, 6, 6', 6" store complex-conjugate spectra, 7, 7', 7" calculate cross spectra, 8, 8', 8" are stored and cross spectra, 9, 9', 9" extend and cross spectra, 10, 10', 10" make the inverse Fourier transform, the blocks 11, 12, 13 stores the processing results for all sorts of mestopolojenie source in the plane is defined at the point of intersection of the hyperbolic lines, corresponding to the received delay.The implementation of the method is illustrated by the following examples.Example 1 (Fig.1). Detection and estimation of the coordinates of the sound source in the pipeline. Z is a function of time relative signal delay from the source to the sensors (microphones). The time delay is indicated by the position of the global maximum of the processing Z with an accuracy that depends on the width of the maximum. Knowing the time delay signal and the speed signal propagation in the environment of the pipeline, determine the coordinates of the source. In Fig. 4 at the same time shows the cross-correlation function (left) and a function of Z, obtained by the proposed method (right) for the case when the audio signal is spread in a linear medium with a speed of 5000 m/s. The result Z clearly indicates that the sound source is at $ 585.4 m Function crosscorrelation has a much broader Central peak, which leads to worse accuracy location the location of the vibration source.Example 2 (Fig. 1). The definition of the coordinate drift over dynamic, randomly inhomogeneous terrain according to the observations of changes in the composition of the terrain. Let some flying machine "hangs" above the cloud pok is Parata on the basis of visual observations of the underlying clouds. Data are consecutive pair of frames of visual images of clouds. In this case, samples f1 and f2 are brightness functions depending on two spatial coordinates. Of course the Fourier transform in the processing units in these cases, two-dimensional. The exit handler is a function of the coordinate shift. Coordinate shift is indicated by the position of the maximum of the processing with accuracy that depends on the width of the global maximum.Example 3 (Fig.2). Active location. Sample f1 is reflected from the target signal, adopted by the antenna. Sample f2 is the reference signal (i.e. the signal radiated in the direction of the goal). The output of the processing unit at the time of maximum (exceeding a certain threshold) indicates the existence of purpose. The width of the Central peak of the maximum determines the accuracy of the measurement of time of arrival at the antenna of the reflected signal and, consequently, the range to the target. If the shape of the signal is known in advance (the signal is not noise-like), can be directly in the processing unit to enter a complex conjugate spectrum of the reference signal; in this case there will be no need for the implementation of the Fourier transform for the implementation of the signal f2. In this way the processing carries out a linear condition is CI, is "nonlinear coherent filter".Example 4 (Fig. 3). Passive location of the seismic source. Even if there is a permanent seismic source on the background of extraneous relatively short-term noise. When a sufficiently large time monitoring, you can determine the coordinates of a permanent source on the earth's surface (i.e., only 2 coordinates). For these measurements establish at least three sensors, which do not lie on the same line. If you are sure that the source lies strictly outside or strictly inside the triangle, the vertices of which are the sensors for evaluation of surface coordinates need 3 sensors. To estimate the spatial coordinates need 4 non-coplanar sensor. In this example, the number of received implementations of course equal to the number of sensors. Using the proposed processing of the measured relative delay for all pairs of sensors. On the basis of known time delays compute the coordinates of the source. Data processing method for detecting a radiation source, comprising converting the first signal into a Fourier spectrum and converting the second signal into a complex-conjugate Fourier spectrum, obtaining mutual is sleduushee inverse Fourier transform of the mutual spectrum characterized in that before the inverse Fourier transform of the mutual range is subjected to expansion by aligning modules amplitudes of its harmonics at a constant, leaving unchanged the sum of squares of amplitudes of all modules harmonics.

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