CN113448346B - Trajectory optimization method based on telemetering information - Google Patents

Abstract

The utility model discloses a trajectory preferred method based on telemetering information, which is characterized by comprising the following steps of: (1) a correlation model of the telemetering angle and the telemetering speed; (2) calculating a correlation model of the remote vision acceleration and the external acceleration; (3) defining a window function; (4) outer trajectory and telemetering information windowing processing; (5) calculating the error of the same telemetering information in each outer ballistic window; (6) calculating the difference value of any trajectory j and the telemetering angle; (7) calculating the correlation difference between the remote vision acceleration and the external acceleration; (8) calculating the error of the same telemetering information in each outer ballistic window; (9) and (4) selecting an optimal trajectory. The trajectory optimization method based on the telemetering information can optimize the external trajectory through credible telemetering parameters, and improves trajectory optimization precision and stability.

Description

Trajectory optimization method based on telemetering information

Technical Field

The utility model relates to the technical field of aerospace outer trajectory processing, in particular to a trajectory optimization method based on telemetering information.

Background

In recent years, various new technologies, new states, and new requirements have been increasingly demanded for the accuracy of the center trajectory of the finger control. The command center has the advantages that the number of real-time trajectories formed by measurement information based on optical equipment, pulse radar equipment, speed measuring radar equipment, remote measuring equipment and the like is large, the total types of errors contained in all trajectories are large, and meanwhile, due to the fact that no unified quality evaluation standard exists, the difficulty in selecting the good trajectory and the bad trajectory is large, and an abnormal trajectory data correction method is lacked.

At present, the method for fusing the trajectory of the command center mainly comprises an optimization fusion algorithm and a weighting fusion algorithm, wherein the method comprises the steps of firstly determining trajectory sequencing by a manual optimization method to form a trajectory optimization sequence frame; secondly, selecting at most n ballistic trajectory parameters at the current moment from ballistic trajectory optimization sequence frames, carrying out difference with the parameters of the previous period to obtain absolute values, and sequencing the absolute values to remove the maximum value and the minimum value; and finally, determining the calculation results of the optimal fusion and the weighted fusion according to the number of the residual trajectories. This preferred method of ballistic trajectory has several major limitations: the selection is mainly carried out by depending on experience and manual operation, and the correctness and the reliability of the selection cannot be completely ensured; the preferred result mainly considers the external information and ignores the remote information.

Disclosure of Invention

The utility model aims to solve the problems, and provides a method based on telemetering information and capable of solving the problem of difficult ballistic preference outside a command center.

In order to achieve the purpose, the utility model adopts the following technical scheme, which comprises the following steps:

(1) correlation model of telemetry angle and telemetry speed: outer ballistic velocity of (v)_x，v_y，v_z) Phi, psi, gamma, alpha and beta are respectively telemetered pitch angle, yaw angle, roll angle, attack angle and sideslip angle, and the calculation formula is as follows:

(2) calculating a correlation model of the remote vision acceleration and the external acceleration: (a)_x，a_y，a_z) For external acceleration measurement, (g)_x，g_y，g_z) Is the component of gravitational acceleration in the launch coordinate system,

to look at the component of the acceleration in the transmit coordinate system, the calculation formula is as follows:

(3) defining a window function: t is the width of the window function, k is a positive integer, k Δ T represents that the function can be shifted along the time axis by an integer multiple of the time interval, and the calculation formula is as follows:

(4) outer trajectory, telemetry information windowing: multiplying the window function defined in step (3) with all outer ballistic, telemetry information;

(5) and calculating the error of the same telemetering information in each outer ballistic window: based on the results of the external ballistic and telemetry information windowing processing in the step (4), when k is equal to 0, the difference between the n external ballistic and telemetry angle functions is as follows:

in the above formula, f₁(v),f₂(v)…f_n(v) And f₁(a),f₂(a)…f_n(a) Respectively an external speed measuring function and an external acceleration measuring function which participate in the preference, g (phi, gamma, alpha, beta) and g (a)_w,g₀) Respectively a function of telemetric angle and a function of telemetric apparent acceleration, T₀Is the zero point of takeoff, and delta T is the sampling interval;

(6) calculating the difference between any trajectory j and the telemetering angle as

In the above formula, M and P are respectively

The mean and variance of (A) are calculated as follows

(7) Calculating the correlation difference between the remote vision acceleration and the external acceleration: when k is 0, the difference between the n ballistic trajectories and the telemetry angle function is calculated as

The difference between any one trajectory j and the telemetry angle is as follows

Wherein M and P are each independently

The mean and variance of (A) are calculated as follows

(8) And (3) calculating the error of the same telemetric information in each outer ballistic window:

(9) selecting an optimal trajectory:

selecting an optimal trajectory based on the error calculation results of the steps (5) to (8) as follows:

p＝min[ΔΨ₁,ΔΨ₂,…,ΔΨ_n]

where min [ ] indicates the minimum error.

The utility model has the beneficial effects that: the utility model provides a trajectory optimization method based on telemetering information, the telemetering information is used as a main parameter for representing the working state of an internal system on an arrow and has a certain coupling relation with external measuring information, the external measuring trajectory can be optimized through credible telemetering parameters, trajectory optimization precision and stability are improved, an association model of key telemetering parameters and external measuring speed parameters is established, a sliding window stepping trajectory optimization method based on the telemetering information is provided, and the external trajectory is optimized.

Drawings

Figure 1 is a schematic view of external ballistic windowing.

Fig. 2 is a diagram of telemetry information windowing.

Fig. 3 is a telemetry calculation result and each external velocity function curve, wherein a diagram (a) is a telemetry angle function curve, and diagrams (b) to (f) are external velocity function curves corresponding to trajectories 1 to 5, respectively.

Detailed Description

The following examples are presented to enable those skilled in the art to more fully understand the present invention and are not intended to limit the utility model in any way.

The utility model is further described with reference to fig. 1 and 2 and is implemented by the following technical solutions.

Taking a rocket as an example, the telemetry T0 time, the external T0 time and the time interval delta T₀And measurement data such as a pitch angle phi, a yaw angle psi, a roll angle gamma, a flight time t, an apparent acceleration component, an aiming azimuth angle, a launching point latitude, an outer trajectory and the like are input.

Step 1), calculating according to the formula in the step 1) to obtain telemetering angle function curves at the left end and the right end of an equation and each external speed function curve;

fig. 3 shows the telemetry calculation result and each external velocity function curve, where fig. 3(a) is a telemetry angle function curve, and fig. 3(b) -3 (f) are external velocity function curves corresponding to trajectory 1-trajectory 5, respectively.

Step 2), calculating according to the formula in the step 2) to obtain an external acceleration curve;

step 3), giving specific definition of the window function;

step 4), windowing external trajectory and telemetering information;

step 5), calculating the error between each trajectory and the telemetering standard curve;

and 6) selecting the trajectory with the minimum error as the optimal trajectory.

Those skilled in the art will appreciate that the above embodiments are merely exemplary embodiments and that various changes, substitutions, and alterations can be made without departing from the spirit and scope of the utility model.

Claims (1)

1. A trajectory optimization method based on telemetering information is characterized by comprising the following steps:

(1) correlation model of telemetry angle and telemetry speed: an outer ballistic velocity of

)，

、

、

、

、

Respectively telemetering a pitch angle, a yaw angle, a rolling angle, an attack angle and a sideslip angle, and calculating formulas are as follows:

；

(2) calculating a correlation model of the remote vision acceleration and the external acceleration: (

) For external measurement of acceleration: (

) As a component of gravitational acceleration in the launch coordinate system, ((ii))

) To look at the component of the acceleration in the transmit coordinate system, the calculation formula is as follows:

；

(3) defining a window function:

is the width of the window function, k is a positive integer,

the expression function may be shifted along the time axis by an integer multiple of the time interval, and is calculated as follows:

；

(4) outer trajectory, telemetry information windowing: multiplying the window function defined in step (3) with all outer ballistic, telemetry information;

(5) and calculating the error of the same telemetering information in each outer ballistic window: windowing the processing result based on the external trajectory and the telemetric information in the step (4), when

Then, the difference between the n outer trajectories and the telemetry angle function is:

，

in the above-mentioned formula,

and

respectively an external speed measurement function and an external acceleration measurement function which participate in the preference,

and

respectively a function of telemetric angle and a function of telemetric apparent acceleration, T₀In order to take-off the zero point,

is the sampling interval;

(6) calculating the difference between any trajectory j and the telemetering angle as

，

In the above formula

And

are respectively as

The mean and variance of (A) are calculated as follows

；

(7) Calculating the correlation difference between the remote vision acceleration and the external acceleration: when in use

Then, the difference value of n ballistic trajectories and the telemetering angle function is calculated as

；

The difference between any one trajectory j and the telemetry angle is as follows

Wherein

And

are respectively as

The mean and variance of (A) are calculated as follows

；

(8) And (3) calculating the error of the same telemetric information in each outer ballistic window:

；

(9) selecting an optimal trajectory:

selecting an optimal trajectory based on the error calculation results of the steps (5) to (8) as follows:

where min [ ] indicates the minimum error.

Images