RU2570115C2 - Guidance of aa medium range missile with active self-guidance head at guidance to group concentrated target - Google Patents

Abstract

FIELD: aircraft engineering.

SUBSTANCE: control over AA mid-range missile with active self-guided head at guidance to the group concentrated target is based on the application of statistic characteristics of the dependence of angular interferences of radar target on its linear sizes. It consists in that the magnitudes of the target angular coordinates are subjected to adaptive filtration by α-β-γ smoothing process and correction algorithm. The magnitudes thus obtained correspond to angular coordinates of actual target of said group target, not to apparent centre which can be located beyond the limits of the location objects geometrical sizes.

EFFECT: higher accuracy of missile guides at negative interference effects.

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Description

The invention relates to guidance systems of anti-aircraft guided missiles (SAM). Considered missiles belong to the class of medium-range missiles with active radar homing. For such missiles, a guidance method is known [1, p. 28], based on the development of control commands in proportion to the mismatch between the position of the equal-signal direction of the antenna of the direction-finding device and the direction to the target. According to this method [1], the antenna of the homing missile head is aimed at an air target (the direction to the target coincides with the equal-signal direction of the antenna), and when the target deviates from the equal-signal direction of the antenna, due to its own motion and the movement of the SAM, the voltage U _D appears at the output of the direction-finding device (t) depending on the magnitude and sign of this deviation. The voltage U _D (t) is further filtered, amplified and transmitted to the actuator to generate missile control commands, while the actuator changes the position of the antenna so that the equal-signal direction moves in space and the initial angular mismatch between it and the direction to the target decreases.

The disadvantages of the method include its insecurity from the negative influence of angular noise of the target in the case of pointing at a group focused target (GSC). GSC is a group target, the elements of which are in the same pulse volume of the tracking direction finder. In the case of pointing the missile to a group target consisting of two or more aircraft, the apparent center of the secondary radiation is always outside the real objects of the location, and when you change the angle of the group target relative to the observation point, this center will wander [2].

The occurrence of bearing errors due to the length of the target leads to the fact that the probability of outputting missiles to the miss tube is significantly reduced. The maximum decrease in probability is observed at a distance of 150-200 m, characteristic of closed battle formations.

The objective of the invention is to develop a method for controlling medium-range missiles with an active homing head when pointing at the HSC, adaptive to intense angular noise, in order to improve the accuracy of pointing the missiles at one of the elements of the hSS.

To solve the problem of the invention, a structure of a control system of an anti-aircraft guided missile shown in FIG. 1. On the drawing are indicated: 1 - device for evaluating the transverse size of the target, 2 - threshold device, 3 - direction-finding device with an antenna, 4 - low-pass filter, 5 - digital α-β-γ filter, 6 - amplifier, 7 - actuator . The proposed structural scheme differs from the original one, which implements the prototype method, by the presence of additional elements 1, 2 and 5, the presence of communication 4-5 and 5-6, in addition, the lack of communication 4-6.

The essence of the proposed method lies in the fact that, in contrast to the known method [1], in order to increase the accuracy of pointing the anti-aircraft guided missile at a group focused target, the received signal from the target received by the antenna of the direction-finding device enters in parallel with the target lateral size estimation device. This device, having estimated the transverse size of the target in a two-stage way [3], generates a tracking index proportional to the transverse size of the target and gives it to the threshold device. In the threshold device, if the tracking index value exceeds the threshold value of the group target attribute, a command is generated to turn on the recursive digital α-β-γ filter (smoothing channel). The voltage U _D (t), proportional to the deviation of the direction of the target from the equal-signal direction of the antenna ε _l , from the output of the low-pass filter enters a recursive digital α-β-γ filter (figure 2), where the analog-to-digital converter converts the voltage U _D (t) into a digital code, which is processed using the transfer functions of the α-β-γ filter with certain coefficients to obtain a smoothed value of the current target coordinates with a compensated fluctuation component.

, $${\stackrel{\mathrm{..}}{\epsilon }}_{л}$$

, приводит к следующему виду уравнений рекурсивного цифрового α-β-γ фильтра:The need to obtain estimates of the coordinates of the target and the parameters of its motion ε _l , $${\stackrel{.}{\epsilon }}_l$$

, $${\stackrel{\mathrm{..}}{\epsilon }}_l$$

leads to the following form of equations of a recursive digital α-β-γ filter:

ε _and [n] = ε _e [n] + αΔε [n]; ε _and [0] = ε ₀ ;

; $${\stackrel{.}{\epsilon }}_{\mathrm{and}}\left[n\right]={\stackrel{.}{\epsilon }}_{\mathrm{uh}}\left[n\right]+\frac{\beta }{T_t}\Delta \epsilon \left[n\right];{\stackrel{\text{.}}{\epsilon }}_{\mathrm{and}}\left[0\right]={\stackrel{.}{\epsilon }}_0$$

;

$${\stackrel{\mathrm{..}}{\epsilon }}_{\mathrm{and}}\left[n\right]={\stackrel{\mathrm{..}}{\epsilon }}_{\mathrm{uh}}\left[n-\mathrm{one}\right]+\frac{\mathrm{<figure-callout\; id="2"\; label="\gamma \; T\; t"\; filenames="00000039.png,00000040.png"\; state="\{\{state\}\}">\gamma \; </figure-callout>}}{T_t^{}}\Delta \epsilon \left[n\right];{\stackrel{\mathrm{..}}{\epsilon }}_{\mathrm{and}}\left[0\right]={\stackrel{\mathrm{..}}{\epsilon }}_0;\text{(one)}$$

; $${\epsilon }_{\mathrm{uh}}\left[n\right]={\epsilon }_{\mathrm{and}}\left[n-\mathrm{one}\right]+T_t{\stackrel{.}{\epsilon }}_{\mathrm{and}}\left[n-\mathrm{one}\right]+\frac{{\mathrm{<figure-callout\; id="2"\; label="T\; t"\; filenames="00000039.png,00000040.png"\; state="\{\{state\}\}">T\; </figure-callout>}}_t^{}}{2}{\stackrel{\mathrm{..}}{\epsilon }}_{\mathrm{and}}\left[n-\mathrm{one}\right]$$

;

, $${\stackrel{.}{\epsilon }}_{\mathrm{uh}}\left[n\right]={\stackrel{.}{\epsilon }}_{\mathrm{and}}\left[n-\mathrm{one}\right]+T_t{\stackrel{\mathrm{..}}{\epsilon }}_{\mathrm{and}}\left[n-\mathrm{one}\right]$$

,

where ε _and [n] is the measured value of the current angular coordinate of the line of sight of the target;

ε _e [n] - extrapolated to the nth step value of the angular coordinate of the line of sight of the target

T _t - the period of the digital missiles;

- вычисленное в n-ном такте угловое ускорение линии визирования; $${\stackrel{\mathrm{..}}{\epsilon }}_{\mathrm{and}}\left[n\right]$$

- the angular acceleration of the line of sight calculated in the n-th clock;

- экстраполированная величина скорости вращения линии визирования; $${\stackrel{.}{\epsilon }}_{\mathrm{uh}}\left[n\right]$$

- extrapolated value of the rotation speed of the line of sight;

α, β, γ are the coefficients of the correction device.

, $${\stackrel{\mathrm{..}}{\epsilon }}_{л}$$

по имеющимся данным и вновь принятым сигналам (Δε[n]). Результаты решения уравнений (1) в виде числовых кодов выдаются потребителям на каждом такте счета. По этим же данным формируются экстраполируемые значения угловых координат линии визирования цели ε_э[n+1] и скорости вращения линии визирования цели $${\stackrel{.}{\epsilon }}_{э}\left[n+1\right]$$

для следующего такта вычислений:Equations (1) represent the operation of a recursive digital α-β-γ filter and describe the procedure for generating the measured values of ε _l , $${\stackrel{.}{\epsilon }}_l$$

, $${\stackrel{\mathrm{..}}{\epsilon }}_l$$

according to available data and newly received signals (Δε [n]). The results of solving equations (1) in the form of numerical codes are given to consumers at each step of the account. According to the same data, extrapolated values of the angular coordinates of the target line of sight ε _e [n + 1] and the rotation speed of the target line of sight are formed $${\stackrel{.}{\epsilon }}_{\mathrm{uh}}\left[n+\mathrm{one}\right]$$

for the following clock cycle:

; $${\epsilon }_{\mathrm{uh}}\left[n+\mathrm{one}\right]={\epsilon }_{\mathrm{and}}\left[n-\mathrm{one}\right]+T_t{\stackrel{.}{\epsilon }}_{\mathrm{and}}\left[n-\mathrm{one}\right]+\frac{{\mathrm{<figure-callout\; id="2"\; label="T\; t"\; filenames="00000039.png,00000040.png"\; state="\{\{state\}\}">T\; </figure-callout>}}_t^{}}{2}{\stackrel{\mathrm{..}}{\epsilon }}_{\mathrm{and}}\left[n\right]$$

;

. $${\stackrel{.}{\epsilon }}_{\mathrm{uh}}\left[n+\mathrm{one}\right]={\stackrel{.}{\epsilon }}_{\mathrm{and}}\left[n\right]+T_t{\stackrel{.}{\epsilon }}_{\mathrm{and}}\left[n\right]$$

.

The mismatch equation on a linear portion of a discriminatory characteristic can be represented as:

Δε [n] = ε [n] -ε _e [n],

The structural diagram of a recursive digital α-β-γ filter (Fig. 2) implies a z-transformation of expressions (1):

Δε (z) = ε (z) -ε _e (z);

; $${\epsilon }_{\mathrm{and}}(z)=z^{-\mathrm{one}}\left({\epsilon }_{\mathrm{and}}(z)+T_t\stackrel{.}{\epsilon }(z)+\frac{{\mathrm{<figure-callout\; id="2"\; label="T\; t"\; filenames="00000039.png,00000040.png"\; state="\{\{state\}\}">T\; </figure-callout>}}_t^{}}{2}\stackrel{\mathrm{..}}{\epsilon }(z)\right)+\alpha \Delta \epsilon (z)$$

;

; $${\stackrel{.}{\epsilon }}_{\mathrm{and}}(z)=z^{-\mathrm{one}}\left({\stackrel{.}{\epsilon }}_{\mathrm{and}}(z)+T_t\stackrel{\mathrm{..}}{\epsilon }(z)\right)+\frac{\beta }{T_t}\Delta \epsilon (z)$$

;

$${\stackrel{\mathrm{..}}{\epsilon }}_{\mathrm{and}}(z)=z^{-\mathrm{one}}\stackrel{\mathrm{..}}{\epsilon }(z)+\frac{\mathrm{<figure-callout\; id="2"\; label="\gamma \; T\; t"\; filenames="00000039.png,00000040.png"\; state="\{\{state\}\}">\gamma \; </figure-callout>}}{T_t^{}}\Delta \epsilon (z);\text{(2)}$$

; $${\epsilon }_{\mathrm{uh}}(z)=z^{-\mathrm{one}}\left({\epsilon }_{\mathrm{and}}(z)+T_t\stackrel{.}{\epsilon }(z)+\frac{{\mathrm{<figure-callout\; id="2"\; label="T\; t"\; filenames="00000039.png,00000040.png"\; state="\{\{state\}\}">T\; </figure-callout>}}_t^{}}{2}\stackrel{\mathrm{..}}{\epsilon }(z)\right)$$

;

, $${\stackrel{.}{\epsilon }}_{\mathrm{uh}}(z)=z^{-\mathrm{one}}\left({\stackrel{.}{\epsilon }}_{\mathrm{and}}(z)+T_t\stackrel{\mathrm{..}}{\epsilon }(z)\right)$$

,

and bringing them to mind:

; $${\epsilon }_{\mathrm{and}}(z)=\frac{z}{z-\mathrm{one}}\left(z^{-\mathrm{one}}{T}_t{\stackrel{.}{\epsilon }}_{\mathrm{and}}(z)+z^{-\mathrm{one}}\frac{{\mathrm{<figure-callout\; id="2"\; label="T\; t"\; filenames="00000039.png,00000040.png"\; state="\{\{state\}\}">T\; </figure-callout>}}_t^{}}{2}\stackrel{\mathrm{..}}{\epsilon }(z)+\alpha \Delta \epsilon (z)\right)$$

;

; $${\stackrel{.}{\epsilon }}_{\mathrm{and}}(z)=\frac{z}{z-\mathrm{one}}\left(z^{-\mathrm{one}}{T}_t{\stackrel{\mathrm{..}}{\epsilon }}_{\mathrm{and}}(z)+z^{-\mathrm{one}}\frac{\beta }{T_t}\Delta \epsilon (z)\right)$$

;

. $${\stackrel{\mathrm{..}}{\epsilon }}_{\mathrm{and}}(z)=\frac{z}{z-\mathrm{one}}\frac{\mathrm{<figure-callout\; id="2"\; label="\gamma \; T\; t"\; filenames="00000039.png,00000040.png"\; state="\{\{state\}\}">\gamma \; </figure-callout>}}{T_t^{}}\Delta \epsilon (z)$$

.

From equations (2), transfer functions of a closed servo system with a recursive digital α-β-γ filter are obtained:

; $$F_{\epsilon }(z)=\frac{{\epsilon }_{\mathrm{and}}(z)}{\epsilon (z)}=\frac{\alpha z^3-\left(2\alpha -\beta -0.5\gamma \right){\mathrm{<figure-callout\; id="2"\; label="z"\; filenames="00000039.png,00000040.png"\; state="\{\{state\}\}">z</figure-callout>}}^2+\left(\alpha -\beta +0.5\gamma \right)z}{z^3-\mathrm{<figure-callout\; id="2"\; label="B\; z"\; filenames="00000039.png,00000040.png"\; state="\{\{state\}\}">B\; </figure-callout>}{z}^{}{}^2+Cz-D}$$

;

$$F_{\epsilon }(z)=\frac{{\epsilon }_{\mathrm{and}}(z)}{\epsilon (z)}=\frac{\beta z^3-\left(\alpha -2\beta \right){\mathrm{<figure-callout\; id="2"\; label="z"\; filenames="00000039.png,00000040.png"\; state="\{\{state\}\}">z</figure-callout>}}^2+\left(\beta -\gamma \right)z)}{z^3-\mathrm{<figure-callout\; id="2"\; label="B\; z"\; filenames="00000039.png,00000040.png"\; state="\{\{state\}\}">B\; </figure-callout>}{z}^{}{}^2+Cz-D}$$

, $$F_{\epsilon }(z)=\frac{{\epsilon }_{\mathrm{and}}(z)}{\epsilon (z)}=\frac{\frac{\mathrm{one}}{{\mathrm{<figure-callout\; id="2"\; label="T\; t"\; filenames="00000039.png,00000040.png"\; state="\{\{state\}\}">T\; </figure-callout>}}_t^{}}\gamma z{\left(z-\mathrm{one}\right)}^2}{z^3-\mathrm{<figure-callout\; id="2"\; label="B\; z"\; filenames="00000039.png,00000040.png"\; state="\{\{state\}\}">B\; </figure-callout>}{z}^{}{}^2+Cz-D}$$

,

where B = 3-α-β-0.5γ, C = 3-2α-β + 0.5γ, D = 1-α.

The stability conditions for the tracking system in angular coordinates are derived based on the analysis of the coefficients of the characteristic polynomial:

Λ (z) = λ _m z ^m + λ _m-1 z ^m-1 + ... + λ ₁ z + λ ₀ ,

For a polynomial of the third degree (m = 3), the filter stability conditions have the form [4]:

$$\left\{\begin{array}{c}{\mathrm{<figure-callout\; id="0"\; label="\lambda "\; filenames="00000041.png"\; state="\{\{state\}\}">\lambda </figure-callout>}}_0+{\lambda }_{\mathrm{one}}+{\mathrm{<figure-callout\; id="2"\; label="\lambda "\; filenames="00000039.png,00000040.png"\; state="\{\{state\}\}">\lambda </figure-callout>}}_2+{\mathrm{<figure-callout\; id="3"\; label="\lambda "\; filenames="00000039.png,00000041.png"\; state="\{\{state\}\}">\lambda </figure-callout>}}_3>0;\\ {\mathrm{<figure-callout\; id="3"\; label="\lambda "\; filenames="00000039.png,00000041.png"\; state="\{\{state\}\}">\lambda </figure-callout>}}_3+{\mathrm{<figure-callout\; id="2"\; label="\lambda "\; filenames="00000039.png,00000040.png"\; state="\{\{state\}\}">\lambda </figure-callout>}}_2+{\lambda }_{\mathrm{one}}+{\mathrm{<figure-callout\; id="0"\; label="\lambda "\; filenames="00000041.png"\; state="\{\{state\}\}">\lambda </figure-callout>}}_0>0;\\ {\lambda }_3\left({\lambda }_3-{\lambda }_{\mathrm{one}}\right)-{\lambda }_0\left({\lambda }_0-{\lambda }_2\right)>0;\\ 3\left({\lambda }_0-{\lambda }_3\right)-{\lambda }_2-{\mathrm{<figure-callout\; id="0"\; label="\lambda "\; filenames="00000041.png"\; state="\{\{state\}\}">\lambda </figure-callout>}}_0>0\end{array}\right\}$$

where λ ₃ = 1, λ ₂ = -B, λ ₁ = C, λ0 = -D

Further calculations give

$$\begin{array}{c}\alpha +\beta <\mathrm{four};\\ 2\alpha +2\beta +\gamma <8;\\ \alpha \beta +\alpha \gamma -2\gamma >0.\end{array}\}$$

In addition, it follows from the principle of physical realizability that the coefficients must meet the condition [4]: α> 0, β≥0, γ≥0.

, вызывающего установившуюся динамическую ошибку, будет приниматься воздействие, содержащее производную третьего порядка, где $${\stackrel{.}{a}}_0=\stackrel{\mathrm{...}}{\epsilon }$$

, - производная углового ускорения линии визирования цели.When determining the steady-state dynamic error, it is necessary to take into account that the tracking system has third-order astatism, therefore, as the simplest standard input action $$D(t)=\frac{{\stackrel{.}{a}}_0}{6}{\mathrm{<figure-callout\; id="3"\; label="t"\; filenames="00000039.png,00000041.png"\; state="\{\{state\}\}">t</figure-callout>}}^3$$

causing a steady-state dynamic error, an action containing a third-order derivative will be accepted, where $${\stackrel{.}{a}}_0=\stackrel{\mathrm{...}}{\epsilon }$$

, is the derivative of the angular acceleration of the line of sight of the target.

After the z-transformation, the input action has the form:

. $$D(Z)=\frac{{\stackrel{.}{a}}_0{T}_t^{3}z({\mathrm{<figure-callout\; id="2"\; label="z"\; filenames="00000039.png,00000040.png"\; state="\{\{state\}\}">z</figure-callout>}}^2+\mathrm{four}z+\mathrm{one})}{6{\left(z-\mathrm{one}\right)}^{\mathrm{four}}}$$

.

The discrete transfer function is mistakenly described by the expression:

. $$W_{\mathrm{about}w}(z)=\mathrm{one}-F_D(z)=\frac{\left(\mathrm{one}-\alpha \right){\left(z+\mathrm{one}\right)}^3}{z^3-\mathrm{<figure-callout\; id="2"\; label="B\; z"\; filenames="00000039.png,00000040.png"\; state="\{\{state\}\}">B\; </figure-callout>}{z}^{}{}^2+Cz-D}$$

.

The steady-state dynamic error takes the form:

. $$\Delta {\epsilon }_{d\mathrm{at}}=\underset{z\to \mathrm{one}}{\lim }\frac{z-\mathrm{one}}{z}{W}_{\mathrm{about}w}(z)D(z)=\frac{\mathrm{one}-\alpha }{\gamma }{\stackrel{.}{a}}_0{\mathrm{<figure-callout\; id="3"\; label="T\; t"\; filenames="00000039.png,00000041.png"\; state="\{\{state\}\}">T\; </figure-callout>}}_t^{}$$

.

A decrease in the dynamic error is achieved by increasing the coefficients α and γ, provided that α <1.

Fluctuation error is determined by a similar technique. The expressions describing the variance of the measurement errors are:

. $$D\epsilon \mathrm{and}=\frac{\beta \left(2{\alpha }^2-3\alpha \beta +2\beta \right)+0.5\alpha \gamma \left(2\alpha +\beta -\mathrm{four}\right)}{\left(\alpha \beta +0.5\alpha \gamma -\gamma \right)\left(\mathrm{four}-2\alpha -\beta \right)}{D}_{\epsilon }$$

.

The main contradiction is that in order to reduce fluctuation errors, the indicated coefficients α, β, and γ should be reduced; however, if the stability conditions are violated, the variances of the measurement errors become infinitely large or negative.

The optimal values of the coefficients α ₀ , β ₀ , γ ₀ must satisfy the following system of equations [4]:

$$\begin{array}{c}\frac{{\mathrm{<figure-callout\; id="0"\; label="\gamma "\; filenames="00000041.png"\; state="\{\{state\}\}">\gamma </figure-callout>}}_0^2}{\mathrm{one}-{\mathrm{<figure-callout\; id="0"\; label="\alpha "\; filenames="00000041.png"\; state="\{\{state\}\}">\alpha </figure-callout>}}_0}=I^2,\\ {\mathrm{<figure-callout\; id="0"\; label="\beta "\; filenames="00000041.png"\; state="\{\{state\}\}">\beta </figure-callout>}}_0=2\left(2-{\alpha }_0\right)-\mathrm{four}\sqrt{\mathrm{one}-{\mathrm{<figure-callout\; id="0"\; label="\alpha "\; filenames="00000041.png"\; state="\{\{state\}\}">\alpha </figure-callout>}}_0},\\ {\mathrm{<figure-callout\; id="0"\; label="\gamma "\; filenames="00000041.png"\; state="\{\{state\}\}">\gamma </figure-callout>}}_0=\frac{{\mathrm{<figure-callout\; id="0"\; label="\beta "\; filenames="00000041.png"\; state="\{\{state\}\}">\beta </figure-callout>}}_0^2}{2{\mathrm{<figure-callout\; id="0"\; label="\alpha "\; filenames="00000041.png"\; state="\{\{state\}\}">\alpha </figure-callout>}}_0}.\end{array}\}\text{(3)}$$

In this system of equations, I is the tracking index characterizing the intensity of the angular noise of the group target, described by the expression:

, $$I=\frac{{\sigma }_{{\stackrel{\mathrm{..}}{\epsilon }}_a}{T}_t^2{D}_c}{M{L}_c}$$

,

where D _c - range to the target;

M - coefficient characterizing the class of the goal;

L _C - assessment of the transverse size of the target.

The results of the numerical solution of the system of equations (3) allow us to choose the optimal values of the coefficients of the recursive digital α-β-γ filter for specific operating conditions of the tracking system (Fig. 3).

The dispersion matrix characterizing the errors of the tracking system with the filter has the form:

$$D_{\alpha \beta \gamma }=\left(\begin{array}{c}{\mathrm{<figure-callout\; id="0"\; label="\alpha "\; filenames="00000041.png"\; state="\{\{state\}\}">\alpha </figure-callout>}}_0\frac{{\beta }_{\text{0}}}{{\text{T}}_{\text{t}}}\frac{{\gamma }_{\text{0}}}{{\mathrm{<figure-callout\; id="2"\; label="T\; t"\; filenames="00000039.png,00000040.png"\; state="\{\{state\}\}">T\; </figure-callout>}}_t^{}}\\ \frac{{\beta }_0}{T_t}\frac{\text{four}{\mathrm{<figure-callout\; id="0"\; label="\alpha "\; filenames="00000041.png"\; state="\{\{state\}\}">\alpha </figure-callout>}}_{\text{0}}{\mathrm{<figure-callout\; id="0"\; label="\beta "\; filenames="00000041.png"\; state="\{\{state\}\}">\beta </figure-callout>}}_0+{\gamma }_0\left({\beta }_0-2{\alpha }_0-\mathrm{four}\right)}{\mathrm{four}{T}_t^2\left(\mathrm{one}-{\alpha }_0\right)}\frac{{\beta }_{\text{0}}\left({\beta }_0-{\alpha }_0\right)}{2T_t^3\left(\mathrm{one}-{\alpha }_0\right)}\\ \frac{{\gamma }_0}{{\mathrm{<figure-callout\; id="2"\; label="T\; t"\; filenames="00000039.png,00000040.png"\; state="\{\{state\}\}">T\; </figure-callout>}}_t^{}}\frac{{\beta }_{\text{0}}\left({\beta }_0-{\gamma }_0\right)}{2T_t^3\left(\mathrm{one}-{\alpha }_0\right)}\frac{{\gamma }_{\text{0}}\left({\beta }_{\text{0}}\text{-}{\gamma }_{\text{0}}\right)}{T_t^{\mathrm{four}}\left(\mathrm{one}-{\alpha }_0\right)}\end{array}\right)D_{\epsilon }$$

The diagonal elements of the matrix characterize the variance of errors in measuring the angular coordinates, the angular velocity of rotation of the line of sight of the target and angular acceleration, and the remaining elements are the correlation moments of communication. For standard errors of measurements the expressions will be correct:

; $${\sigma }_{{\epsilon }_{\mathrm{and}}}=\sqrt{{\mathrm{<figure-callout\; id="0"\; label="\alpha "\; filenames="00000041.png"\; state="\{\{state\}\}">\alpha </figure-callout>}}_0{\sigma }_D}$$

;

; $${\sigma }_{{\stackrel{.}{\epsilon }}_{\mathrm{and}}}=\sqrt{\frac{\mathrm{four}{\mathrm{<figure-callout\; id="0"\; label="\alpha "\; filenames="00000041.png"\; state="\{\{state\}\}">\alpha </figure-callout>}}_0{\mathrm{<figure-callout\; id="0"\; label="\beta "\; filenames="00000041.png"\; state="\{\{state\}\}">\beta </figure-callout>}}_0={\gamma }_0\left({\beta }_0-2{\alpha }_0-\mathrm{four}\right)}{\mathrm{four}{T}_t^2\left(\mathrm{one}-{\alpha }_0\right)}}{\sigma }_D$$

;

, $${\sigma }_{{\stackrel{\mathrm{..}}{\epsilon }}_{\mathrm{and}}}=\sqrt{\frac{{\gamma }_0\left({\beta }_0-{\alpha }_0\right)}{T_t^{\mathrm{four}}\left(\mathrm{one}-{\alpha }_0\right)}}{\sigma }_D$$

,

- среднеквадратическое значение дискретного белого шума, характеризующего возмущающее воздействие (шум наблюдения).Where $${\sigma }_D=\sqrt{D_{\epsilon }}$$

- the rms value of the discrete white noise characterizing the disturbing effect (observation noise).

In the correction channel, according to the data obtained after measuring the size of the GSC, a correction signal is generated proportional to the size of the target. The value of the correction for the true position of the target is chosen equal to

, $$\Delta =\pm k_h\frac{L_c}{2}\left(\mathrm{one}-e^{arctg\left(-\frac{L_c}{2r_l}\right)}\right)$$

,

where k _h = 0.337 1 / m, and the sign of the correction is determined by the sign of the tracking error of the coordinator and the position of the guidance object relative to the CC.

In order to verify the operability of the proposed method, mathematical modeling was carried out using a simulation mathematical model of a control system for an anti-aircraft guided missile with a homing radar [5] and mathematical models of real air targets [4]. The simulation results showed that the application of this method allows to increase the accuracy of guidance of anti-aircraft guided missiles when firing at a group target by 50-60% (figure 4). Figure 4 shows the reduction in missiles missiles with an α-β-γ filter when firing at the GCC with a burst of two missiles at the first and second targets (a - the first missile, b - the second missile).

Thus, the proposed method made it possible to obtain smoothed values of the angular coordinates of a group focused target, reducing the negative effect of angular noise.

Information sources

1. Pervachev S.V. Radio Automation. M .: Radio and communications, 1982. 175 p.

2. Ostrovityanov R.V., Basalov F.A. Statistical theory of radar extended targets. M., Radio and Communications, 1982.- 232 p.

3. Chertkov EV Analysis of the accuracy characteristics of the two-stage method for assessing the geometric dimensions of airborne objects. Dep. manuscript in the Center M.: TsVNI MO RF, ser. B, no. 59, 2002. - 11 p.

4. Zharkov S.V. The use of adaptive digital filters in the tracking direction finders of anti-aircraft systems. // Scientific. tr academy. Smolensk, 1996. Issue. 5. S. 63-69.

5. Certificate of official registration of the computer program. M., OFERNiO No. 16972. 2011. Control system for anti-aircraft guided medium-range missiles / Zharkov SV, Kaduchenko IV

Claims (1)

A method of controlling an anti-aircraft guided medium-range missile with an active homing head when pointing at a group focused target (HSS), which consists in the fact that the antenna of the homing anti-aircraft guided missile is directed at a group focused target (the direction to the target coincides with the antenna's equal signal direction), and when deviation of the target from the equal-signal direction of the antenna (due to its own motion and the movement of the anti-aircraft guided missile), at the output of the direction-finding device appears on voltage was U _L (t), depending on the magnitude and sign of the deviation, a voltage U _L (t) is filtered, amplified and transmitted to an actuator, for generating flight control commands surface-to-air missile, changes the position wherein the actuator of the antenna so that the beams the direction shifts in space and the initial angular mismatch between it and the direction to the target decreases,
characterized in that the signal from the target received by the antenna of the direction-finding device enters in parallel to the target lateral size estimation device, where the lateral target size is estimated and the tracking index is formed (proportional to the transverse target size), the tracking index is transmitted to the threshold device, in which, in in case of exceeding the tracking index value of the threshold value of the group target attribute, a command is generated to turn on the recursive digital α-β-γ filter (the channel is smoothed Nia), a value U _A (t) after the low pass filter enters the recursive digital α-β-γ filter, wherein the analog-digital converter converts the voltage U _R (t) to a digital code, which via the transmission filter functions with optimal coefficients processed to obtain a smoothed value of the current coordinates of the target with a compensated fluctuation component, in the correction channel, according to the data obtained after measuring the size of the GSC, a correction signal is generated proportional to the size of the target, the obtained values through digital -analog converter is fed to the actuator to generate commands for controlling an anti-aircraft guided missile and turning the antenna.

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