RU2710894C1 - Method of classification and blanking of discrete interference - Google Patents

Abstract

FIELD: radar ranging and radio navigation.

SUBSTANCE: invention relates to radio engineering, particularly to digital processing of radar signals. Invention is characterized by evaluating longitudinal size of classified objects and size that does not exceed threshold is classified as interfering signal by correlation feature, estimating power of received signals, which is compared with a threshold in each range element with assignment of interfering signal characteristic signal when the threshold is not exceeded in a certain range element, at that, after combining correlation, velocity and ERA indications of interfering signal at their coincidence, decision is made on blanking of reflected signal in given range element.

EFFECT: invention is intended to increase efficiency of classification and blanking of discrete passive jamming.

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Description

The present invention relates to radio engineering, in particular, to digital processing of radar signals.

A known method of blanking signals of discrete interfering reflections, based on the formation of the so-called "frequency threshold", actually a speed threshold, not exceeding which is classified as a sign of the signal reflected from the interfering point object with a small radial velocity in this range element [1]. Therefore, this signal is blanked, reducing the flow of false marks at the output of the radar receiving path. The main disadvantage of this method is its low efficiency, due to the need to use for an unambiguous measurement of the speed of a wobbled burst with a limited number of pulses. In addition, an attempt to set the maximum high speed threshold to increase the effectiveness of this method leads to an increase in the likelihood of blanking useful targets at a low radial speed.

The closest in technical essence to the claimed method is a two-frequency method for classifying and blanking discrete correlated interference. This method is based on processing the reflected signals at each carrier frequency of the radar in the form of two observation samples in each element of range and includes the formation of estimates of the inter-period Doppler phase difference with their subsequent subtraction for unambiguous measurement of the speed of a discrete detected object [2]. The thus obtained estimate of the interfrequency interperiodic phase difference is compared with the phase threshold (in fact, with the velocity threshold), on the basis of which a decision is made to blank the reflected signals from slowly moving interfering point objects if this threshold is not exceeded. Although this method allows a more efficient classification of signals due to the higher accuracy of estimating the interperiodic phase difference at each carrier frequency of the radar, due to the absence of wobble period repetition using a larger number of pulses, nevertheless, this method has the disadvantage of blanking useful targets with small radial speeds.

The known method [3], in which to eliminate the blanking of useful signals from targets with low radial velocities for signals received at two carrier frequencies, they are carried out as forming estimates of the inter-frequency inter-period Doppler phase difference to unambiguously measure the speed of objects in each range element and compare this estimate with a threshold , if not exceeding which, the detected signal is classified according to the speed criterion as interfering and the formation of the module of the inter-frequency correlation coefficient, which th is used to estimate the longitudinal size of the classified objects and which, if the threshold is not exceeded, is classified as an interfering signal according to the correlation sign, while the velocity and correlation signs for interfering reflections are assigned logical units, the coincidence of which is recorded in each element of the range using the logical function "AND ", On the basis of which a decision is made to blank the reflected signal in this range element. Although this method allows using the speed and correlation features to increase the efficiency of blanking of interfering reflections, however, not taking into account the power of the reflected signal can lead to an erroneous classification when signals from a target with a small radial speed and large size, for example, a flying airliner, can be taken as interfering from the perspective of the radar.

In order to eliminate the blanking of useful signals from targets with low radial velocities and a large longitudinal size, a method is proposed that includes, as in the prototype, the formation of estimates of the inter-frequency inter-period Doppler phase difference for unambiguous measurement of the speed of objects based on two observation samples taken on two carrier frequencies and comparing this estimate with a threshold in each element of the range with the assignment if this threshold is not exceeded in a specific element of the range of the sign of the signal interfering about reflection, also the formation of the module of the inter-frequency correlation coefficient, which is used to estimate the longitudinal size of the classified objects and which, without exceeding the threshold, is classified as an interfering signal by the correlation feature, characterized in that in order to exclude blanking of useful signals from targets with a large effective scattering surface ( EPR), an estimate of the power of the received signals is formed, which is compared with a threshold in each element of the range with the assignment if this threshold is not exceeded and a particular element of the interfering signal reflection characteristic range, wherein after combining the correlation, speed ESR characteristics of the interfering signal upon the coincidence decision on blanking reflected signal range in a given element.

The threshold of the EPR of the attribute varies in distance for each element of range in accordance with the equation of the range of the radar for the selected EPR of interfering reflection and specific parameters of the radar.

At this threshold, an averaged signal is fed in each element of the range, both over the signal packet of each frequency channel, and their sum. EPR estimation from measurements of the received signal power is determined by the well-known formula of the equation for the range of radar [4]

where σ is the value of the EPR;

Rpr is the power of the received signal;

Rper - transmitter power;

G is the gain of the transmitting (receiving) antenna;

λ is the radar wavelength;

R is the range to the target.

Thus, the proposed method reveals new functionality for classifying and blanking discrete interference and eliminates the blanking of small-sized useful targets having low radial speeds, large longitudinal size and high EPR. This allows us to conclude that the proposed method meets the criterion of "significant differences".

Indeed, in the method taken as a prototype, for an unambiguous measurement of the speed of the detected object on each carrier, an estimate of the inter-period Doppler phase difference is formed with the subsequent formation of the inter-frequency inter-period phase difference.

To classify objects according to the speed attribute, one can use the well-known estimate of the argument of the inter-period correlation coefficient. The algorithm for this estimate, obtained from a pack of N pulses, can be expressed as follows

z_i - комплексные выборки наблюдений на одной несущей частоте.Where

z _i are complex samples of observations at one carrier frequency.

The classification of objects according to the speed criterion can be implemented by comparing the obtained estimate with a threshold corresponding to the maximum speed of the interfering object

The use of such a single-frequency classification algorithm is fraught with a significant drawback - the presence of ambiguity in estimating the Doppler phase. It is known that the estimate of γ is associated with the radar wavelength λ of the radar, the pulse repetition rate F, and the radial component of the object’s flight speed V as

At relatively small values of the repetition frequencies (F = 300 Hz - 1000 Hz), which are used in most modern radar detection, γ can several times exceed the value 2π even in the case of probing the radar of a slowly moving object, while the arctangent function is uniquely determined in interval of phase change from 0 to 2π (or from - π to π). This can lead to an increase in the probability of erroneous classification of high-speed and slow-moving objects. To eliminate this drawback in the prototype uses two carrier frequency radar. The Doppler phase incursion at each of the carrier frequencies can be represented as

γ₁= γ₁₀+ 2πk, γ₂= γ₂₀+2 πn, where γ₁₀, γ₂₀ - phase values in the uniqueness interval (- π, π), k, n = 0, 1, 2, ..., ∞.

We determine the interfrequency phase difference:

Δγ = γ ₁ -γ ₂ = γ ₁₀ -γ ₂₀ + 2πk-2πn

For a small separation of carrier frequencies (a few% of the carrier) k = n, we obtain

Δγ = γ ₁₀ -γ ₂₀ , The difference Δγ is uniquely defined within

(-π, π).

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Thus, the algorithm for unambiguous measurement of the phase difference

will be

Where

The measured inter-frequency difference of the inter-period phase difference is compared with a threshold and, if the threshold is not exceeded, a decision is made that the reflected signal belongs to the signals of point interfering reflections and is blanked. So we used the estimation of the inter-frequency inter-period phase difference in the method taken as a prototype, in which the evaluation of the inter-frequency inter-period phase difference by comparing with the threshold forms only the first speed sign, for example, in the form of a logical unit, if the threshold is not exceeded. Additionally, in the prototype, the use of two carrier frequencies for an unambiguous measurement of speed makes it possible to form another sign of a classified object - inter-frequency correlation coefficient. As shown in [5]

To classify the reflected signals from objects according to their longitudinal size, one can use the nature of fluctuations of the reflected signals at different carrier frequencies. In particular, the basis of the second classification feature in the proposed method is the relationship of the normalized inter-frequency correlation coefficient with the linear dimensions of the object. The larger the size of the object, the lower the inter-frequency correlation coefficient. If the carrier spacing is selected from the condition

где L_MAX - максимальный разнос участков локального отражения вдоль линии визирования РЛС на классифицируемый объект при разных несущих частотах зондирующего сигнала, то величина межчастотного коэффициента корреляции R(ΔF) будет связана с размером объекта L выражением

where L _MAX is the maximum separation of the local reflection sections along the radar line of sight to the classified object at different carrier frequencies of the probe signal, then the magnitude of the inter-frequency correlation coefficient R (ΔF) will be related to the size of the object L by the expression

As follows from this formula from [5], in order to distinguish between a class of aircraft with a small longitudinal size and a class of slowly moving discrete interfering objects having significantly large sizes L, it suffices to choose a carrier spacing ΔF of the order of 10 MHz. Modern aircraft have a maximum size of less than 75 meters, which is significantly less than the resolution of the radar detection component of 150-300 meters, commensurate with the size of discrete passive interference.

In this case, for the largest aircraft, for example, Airbus A-380, measuring 72 meters in size, the inter-frequency correlation coefficient is

For a smaller size of the domestic airliner IL-96-300 55 meters long

While for a 200 meter interfering object

This means that by choosing a carrier spacing of not more than 10 MHz and comparing the correlation sign with the threshold, if it is not exceeded, a second logical unit of the correlation sign is formed.

Combining the logical signs according to the “AND” when the logical units coincide, a decision is made to blank the signal reflected by the interfering object in this range element.

It should be noted that the carrier spacing of 10 MHz is in good agreement with the requirement of an unambiguous estimate and a speed attribute, i.e. makes up several percent of the carrier frequency of modern radar surveys.

As for the first speed feature, for the formation of the interfrequency correlation coefficient, we apply the accumulation of estimates from a pack of N pulses.

where z _1i and z _2i are complex samples of observations at the first and second carrier frequencies. Then the inter-frequency correlation coefficient can be calculated by the following formula:

In contrast to the prototype with speed and correlation features, in order to eliminate the blanking of useful signals with a large EPR, it is proposed to use a third EPR sign, which can be obtained by summing the powers of the signals z1 and z2 used to normalize the estimates of the inter-frequency correlation coefficient, i.e.

z1 + z2 <σ _POR

We illustrate the work of the proposed method with a specific example, resorting to modeling using the MATLAB system [6].

We will classify two objects moving at a speed of 10 to 180 meters per second, using two observation samples in the form of two bursts of pulses with a constant repetition period of 0.001 seconds, reflected from the object at different carrier frequencies of 500 MHz and 510 MHz. The objects have a width of the fluctuation spectrum of several hertz and a large longitudinal size, characterized by an inter-frequency correlation coefficient of 0.1 (both the target and the interfering object). The velocity threshold was set at 100 m / s and the correlation threshold was 0.5. The processed number of pulses per burst on each carrier was 8. Assume that the ESR of the target is σ1 = 5 m ² , and the interfering reflection of the ESR is σ2 = 0.25 m ² . In general terms, the radar range equation follows

- constant coefficient characterizing the radar parameters,

where P _CR1 , P _CR2 is the power of the received signal at the input of the receiving antenna at a range of R ₁ and R _2, respectively.

Using (2) and (3), we find the ratio of the EPR estimates made at different ranges R ₁ and R ₂ :

Assuming that the useful target and interfering reflections are at the same range, it can be seen that the power of the received signals for the selected EPR differs by 20 times. Let us take the dispersion of simulated quadrature components with a Gaussian distribution law for interfering reflections equal to 1, and for the target twenty times more. The results of modeling the probabilities of blanking these objects in MATLAB using the proposed method (marked with asterisks) and the method taken as a prototype (marked with circles) are shown in FIG. 1 and FIG. 2. In FIG. Figure 1 shows the probability of blanking an object with a small EPR having large longitudinal dimensions (the threshold of 0.5 by estimating the inter-frequency correlation coefficient is not exceeded by them) and low speeds. The probability of blanking for the proposed method coincides with the prototype, since the EPR threshold by the received signal power is not exceeded. In FIG. Figure 2 shows the probability of blanking for an object with a large EPR with a large longitudinal size and low speeds, the reflected signals from which are not blanked for the proposed method, but are blanked from the method taken as a prototype. In the prototype, due to the lack of an EPR sign, both interfering reflections and a useful target are blanked out. In other words, the proposed method has clear advantages over the previously known.

Thus, the study in the MATLAB system fully confirms the positive effect of the application of the proposed method for classifying and blanking discrete interference.

LIST OF SOURCES USED WHEN FORMING THE APPLICATION

1. Lozovsky I.F. Surveillance radar protection against point interference. - Novosibirsk: NSTU Publishing House, 2014.

2. Bartenev V.G., Galkin R.N. Synthesis of a digital two-frequency classifier of discrete interference by speed attribute. - Proceedings of the 16th International Conference “Digital Signal Processing and its Application DSPA-2014”, Moscow, T. - 1, p. 343-347, 2014.

3. Bartenev V.G. A method for classifying and blanking discrete interference. Patent No. 2599870 but application No. 2015128907 is registered in the State Register of the Russian Federation on September 23, 2016.

4. Reference radar. Ed. M. Skolnik, vol. 1, M., "Soviet Radio", 1976, p. 357, formula (1).

5. Abramenkov VV, Klimov S. A., Bondarev P. A., Yudin V. A., Gulshin V. A. Resolution and recognition of radar objects - Ulyanovsk: UlSTU, 2012.

6. Potemkin V.G. "MATLAB Handbook Data Analysis and Processing, http: / matlab.exponenta.ru/ml/book2/chapter8/

Claims (3)

1. A method for classifying and blanking discrete interference, which includes generating estimates of the inter-frequency inter-period Doppler phase difference for unambiguous measurement of the speed of objects based on two samples of observations received at two carrier frequencies, and comparing this estimate with a threshold in each element of range with assignment at not exceeding this threshold in a particular element of the range of the sign of the signal of interfering reflection, the formation of the module of the inter-frequency correlation coefficient, which is used to estimate the longitudinal size of the classified objects and which, without exceeding the threshold, is classified as an interfering signal according to the correlation feature, characterized in that in order to exclude the blanking of useful signals from targets with a large effective scattering surface (EPR), an estimate of the received signal power is formed, which is compared with the threshold in each element of the range with the assignment if this threshold is not exceeded in a specific element of the range of the sign of the signal of interfering reflection, while after combining the correlation nnogo, speed and the ESR characteristics of the interfering signal upon the coincidence decision on blanking reflected signal range in a given element. 2. The method according to p. 1, characterized in that the threshold of the EPR of the characteristic varies in distance for each element of range in accordance with the equation of the range of the radar for the selected EPR of interfering reflection and specific parameters of the radar. 3. The method according to p. 1, characterized in that for interfering reflections according to speed, correlation and EPR signs, logical units are assigned and their coincidence is fixed in each element of range using the logical function "AND".

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