RU126474U1 - PASSIVE RADIO ELECTRON COMPLEX FOR DETERMINING SPATIAL COORDINATES AND OBJECTS OF MOTION OF THE OBJECT BY ALGOMERIC AND POWER RADAR DATA - Google Patents

Abstract

A passive electronic complex for determining the spatial coordinates and elements of the object’s motion using the goniometric and energy data of the radar, containing an antenna, a unit for detecting signals on the direction-finding channel, a unit for tracking the object in the direction-finding channel, a block of statistical estimates of the initial bearing, the initial signal level, the initial magnitude of the change in bearing the initial value of the distance change, the software implementation block of Kalman filters, the unit for estimating the coordinates and elements of the object’s movement, the block in information output to the screen and information output unit to user banks, characterized in that the complex includes a signal detection unit for an elevation channel, an object tracking unit in an elevation channel, a unit for measuring the elevation angle to the object and signal levels from the object, a unit for calculating angle estimates the location and signal levels in the elevation channel and the unit for calculating the magnitude of the change in elevation angle, while the signals from the object received by the antenna are processed in the signal detection unit through the direction-finding channel and in the detection unit signals along the elevation channel for subsequent tracking of the object, respectively, in the tracking unit of the object in the bearing channel and in the tracking unit of the object in the elevating channel, then the signals from the tracking unit of the object in the bearing channel are sent to the block of statistical estimates of the initial bearing, the initial signal level, the initial change the bearing and the initial value of the distance change, and the signals from the object tracking unit in the goniometer channel to the unit for measuring the elevation angle to the object and the signal levels

Description

The utility model relates to the field of radar and radio navigation and can be used to determine the coordinates and elements of the object’s movement using a passive radio-electronic complex (PREC) installed on a single carrier.

The purpose of the utility model is to increase the functionality of PREC, by providing the ability to determine the spatial coordinates and elements of motion of various objects by a single carrier, without emitting active radar signals.

State of the art

A measurement device is known consisting of a radar with a uniform cyclic overview, in which each single observation (one review cycle) is a collection of random signals containing information about the current implementation of the stream of objects. These signals, after appropriate processing, by means of blocks for various purposes, can be represented as a set of random points, each of which is characterized by a certain set of parameters. (P.A. Bakut, Yu.V. Zhilina, N. A. Ivanchuk. Detection of moving objects. Moscow, Soviet Radio 1980 p. 94-96) [1].

The disadvantages of the known device include the operation of the radar station in active mode, which unmasks the carrier, as well as the inability to determine the distance to the object in passive mode with a single carrier.

For the prototype, a passive radio-electronic complex (PREC) was chosen for the on-off determination of horizontal coordinates and elements of the object’s motion by the linear Kalman – Bucy filtering method according to the RF patent for utility model No. 112446, IPC G01S 11/12, G01S 5/00, 2011, publ. 01/10/2012, bull. No. 1 [2].

The complex - the prototype contains an antenna, a radar signal detection unit (a signal detection unit by a bearing *, ^*) - hereinafter referred to in the claimed PREC), a signal and bearing measurement unit, a bearing tracking signal unit (an object tracking unit in a bearing channel *) a statistical evaluation unit bearing primary (P _o), the initial value changes bearing (TTI _o) and the initial value of the distance change (VIR _o) (block statistical estimates primary bearing, the initial signal level of the initial the magnitude of the change in the bearing and the initial magnitude of the change in the distance *), the block for constructing the set of Kalman filters (block for the software implementation of Kalman filters *), the block for estimating the distance to the target and the elements of movement of the object (ED) (block for estimating coordinates and ED *), screen (output unit information on the screen *) and the current situation lighting unit (the unit for issuing information to user banks *).

Complex - prototype works as follows.

The antenna continuously receives radiation from the object, the signals are processed by the radar signal detection unit and fed to the signal and bearing measurement unit, the received bearing values are sent to the signal tracking unit in which the bearing sequence is formed, which is necessary to obtain statistical estimates of P _o , VIP _o and VIR _on a statistical evaluation _{of the} block P, VIP and _about VIR _of obtained evaluation together with measured signal levels to enable the block construction of the set of filters Feces ana to construct a set of Kalman filters for coordinate assessments and EDI in the block estimation the distance to the object and EDI on the basis of these coordinates, which are displayed on the screen, data is generated in the block of the current situation of illumination for operational decisions.

The essence of the complex-prototype operation is the passive measurement of the horizontal coordinates of a moving object when assessing the change in the level of the received signal during observation and bearing to the target using PREC and is true for objects operating in the centimeter wavelength range, the initial values of the three-dimensional state vector are calculated from the measured bearing the target containing the bearing (P), the magnitude of the change in the bearing (VIP), the magnitude of the change in distance (VIR), which after measuring the signal power allows grammed four-dimensional state vector of the object, comprising besides these three values, and even the distance to the object in the further bearing on the measurement object signal and a power via the Kalman filter is determined coordinates and EDI for planar task.

The disadvantage of the complex prototype is its low functionality due to the impossibility of solving the spatial problem, i.e. the impossibility of determining, apart from the bearing and distance, also the elevation angle of the object.

This goal is achieved by the fact that by expanding the measured information space in the PREC, in addition to determining the elements of the four-dimensional state vector, which includes the bearing, the magnitude of the change in the bearing, the magnitude of the change in the distance and the distance to the object, determine the elements of the six-dimensional state vector, which includes the bearing, the value changes in the bearing, the magnitude of the change in distance, the distance to the object, the elevation angle of the object and the magnitude of the change in elevation angle, due to the sequence of measured signal levels and the channel measurements and channel bearing measurement object elevation angle jointly with a sequence of measured bearings and angle of the object place.

The task to which the utility model is directed

Difficulties are known in determining the distance to ultra-long objects by multi-position systems by goniometric measurements, but for a single-position passive system, this problem cannot be solved by existing methods and devices for their implementation.

In the claimed solution, the filtering of the coordinates of the object is carried out with the involvement of additional information with the subsequent application of adaptive algorithms for processing existing data. With such a statement of the problem, it is possible in principle to limit oneself to considering the relative motion of two bodies — the object and the observer.

The object is observed by PREC in the tracking mode, and both the object and the observer make uniform rectilinear motion.

The model of the bearing change in time has the form:

Where:

P ₀ - bearing of the target at the initial time,

- величина изменения пеленга в начальный момент времени,

- the magnitude of the change in the bearing at the initial time,

- величина относительного изменения дистанции в началь-ный момент времени,

- the magnitude of the relative change in distance at the initial time,

- величина изменения дистанции в начальный момент времени,

- the magnitude of the change in distance at the initial time,

D ₀ - distance to the object at the initial time,

t is the current time,

t ₀ - the initial moment of time, hereinafter (tt ₀ ) is denoted by t.

The model of changing the elevation angle of the target in time has the form:

Where:

ν ₀ - elevation at the initial time,

- величина изменения угла места в начальный момент времени.

- the magnitude of the change in elevation at the initial time.

It is known that by measuring only the angles P and ν it is impossible to determine the distance to the object without a special maneuver with a single-position observation system.

To solve the problem of determining the distance to an object by a single-position observer, it is necessary to use additional information, which is a sequence of measured signal levels (powers).

A typical situation is the measurement of П and ν by various devices included in a single tracking complex for an object.

Then the measurement in time of the centered signal level in the channel (device) of measurement P has the form:

Where:

P _t is the power of the received signal at the current time,

- мощность принятого сигнала в начальный момент времени.

- the power of the received signal at the initial time.

Where:

D ₀ - distance to the object at the initial time,

δ is the coefficient of kilometric attenuation of the signal on the path of the object - observer.

At the same time, the change in time of the centered signal level in the measurement channel v has the form:

Analysis of measurement equations 1-4 allows us to determine the six-dimensional state vector

Where:

X is the state vector,

x ₁ -x ₆ are the components of the state vector,

T is the transpose sign of the vector.

The equation of state in this case has the form:

Where:

X _{i + 1} - state vector at time t _{i + 1} ,

X _i is the state vector at time t _i .

Since the measurement equations 1–4 are nonlinear with respect to the components of the state vector, it is necessary to linearize these equations in the vicinity of some a priori estimate of the state vector.

The more accurate this a priori estimation of the state vector is, the faster the convergence of further estimates (in the Kalman filtering process) to the true value of the state vector will be.

The equations of Kalman filtration (six-dimensional state vector, four-dimensional measurement vector) have the form:

Where:

,

- оценки вектора состояния на i-й и (i+1)-й моменты времени соответственно,

,

- estimates of the state vector at the i-th and (i + 1) -th time moments, respectively,

cov X _i , cov X _{i + 1} - estimates of the covariance matrix of the state vector at the i-th and (i + 1) -th time moments, respectively,

- градиент функции

в grad

- function gradient

at

(i + 1) -th moment of time,

- градиент функции

вgrad

- function gradient

at

(i + 1) -th moment of time,

σ is the standard deviation

- градиент функции

вgradU

- function gradient

at

(i + 1) -th moment of time,

- градиент функции

вgradU

- function gradient

at

(i + 1) -th moment of time,

П _{i + 1} , ν _{i + 1} , U _{П, i + 1} , U _{ν, i + 1} - measurements of bearing, elevation, centered signal level in the bearing measurement path, centered signal level in the elevation measurement path, respectively,

P (X _{i + 1} ), ν (X _{i + 1} ), U _P (X _{i + 1} ), U _ν (X _{i + 1} ) - forecasts of bearing, elevation angle, centered level in the measurement channel of the bearing, centered level in channel locations respectively

10

At regulated time intervals, it is necessary to recalculate the state vector from the initial moment of time to the current moment of time.

Recalculation Formulas:

Recalculation of the covariance matrix of the state vector from the initial moment t ₀ to the current moment t is carried out according to the formula:

Where:

Utility Model Essence

The essence of the claimed utility model is that the PREC was developed for passive measurement of the spatial coordinates of moving objects according to estimates of the level of the received signal in the process of observing the object together with estimates of the bearing and elevation of the object in the corresponding channels.

PREC does not require performing special maneuvers of the carrier of a location-measuring instrument or involving other carriers, which are usually used in traditional methods for determining the location of radiation sources of radio waves.

PREC can be used in spatial radar and radio navigation of artificial Earth satellites and other spacecraft for target designation, determining the spatial coordinates of flying missiles and aircraft, as well as the position of ground-emitting radars from flying objects.

The utility model is illustrated by the structural diagram, where:

1 - antenna

2 - signal detection unit on the bearing channel,

3 - block detection signals in the elevation channel,

4 - unit tracking object in the bearing channel,

5 - unit tracking object in elevation channel,

6 is a block of statistical estimates of the initial bearing (P ₀ ), the initial signal level (U ₀ ), the initial value of the bearing change (VIP ₀ ) and the initial value of the distance change (VIR ₀ ),

7 - unit for measuring the elevation angle to the object and signal levels from the object,

8 is a block for calculating estimates of elevation angle and signal levels in the elevation channel,

9 is a block calculating estimates of the magnitude of the change in elevation angle (VIUM),

10 is a block software implementation of Kalman filters,

11 - unit for estimating coordinates (distance D, bearing P and elevation angle ν) and elements of the object’s movement (speed V, course K, magnitude of change in bearing of VIP, magnitude of change in distance VIR and magnitude of change in elevation of VIUM),

12 - block display information on the screen,

13 is a block for issuing information to user banks.

Utility Model Implementation

The utility model is implemented as follows.

The signals from the object received by the antenna 1 are processed in the signal detection unit on the bearing channel 2 and in the signal detection unit on the elevation channel 3 for subsequent tracking of the object, respectively, in the object tracking unit in the bearing channel 4 and in the object tracking unit in the elevation channel 5, further, the signals from block 4 enter the block of statistical estimates of the initial bearing, the initial signal level, the initial magnitude of the change in bearing and the initial magnitude of the change in distance 6, and the signals from block 5 - in b lock measuring elevation angle to the object and signal levels from object 7, to the calculation unit of the estimates of the elevation angle and signal levels in the elevation channel 8 and to the calculation unit of the estimates of the magnitude of the change in elevation 9, the calculated estimates provide the construction of many Kalman filters in the software implementation block of Kalman filters 10 for the subsequent receipt in the unit of estimation of coordinates and elements of the object’s movement 11 current coordinates estimates - distance, bearing and elevation and elements of the object’s movement - speed, course, magnitude of the bearing change, led ranks changing the distance and the amount of change of the elevation angle, then the resulting data is supplied to block output of information on the screen 12 and a data output unit in banks members 13 for illumination of the current situation and making operative solutions.

The input information for determining the coordinates can be the output forms of the object tracking system in the passive channels of radar stations. The implementation of the utility model can be performed by implementing the implementation of the algorithm in the software of the workstations or by manufacturing a computing unit - a set-top box for existing radars, provided that the radar of bearings, signal levels and elevation angles of the object are measured.

It is possible to manufacture a separate unit - a prefix, which, after setting up the input, can solve the problem of determining spatial coordinates in the passive mode.

The technical result from the introduction of a utility model is to provide the possibility of estimating spatial coordinates when observing an object with a single-position PREC in a stealth mode of tracking.

The specified technical result is achieved by a combination of distinctive features, namely the introduction of a unit for detecting signals on the elevation channel, a unit for tracking the object in the elevation channel, a unit for measuring the elevation angle to the object and signal levels from the object, and a unit for computing estimates of elevation angle and signal levels in elevation channel and unit for calculating the magnitude of the change in elevation angle.

The presented description and structural diagram of the inventive passive electronic complex allow, using purchased components, existing materials and equipment, to manufacture it industrially and use it to determine the coordinates - distance, bearing and elevation and elements of the object’s movement - speed, course, magnitude of bearing change, the magnitude of the change in distance and the magnitude of the change in elevation.

Claims (1)

A passive electronic complex for determining the spatial coordinates and elements of the object’s motion using the goniometric and energy data of the radar, containing an antenna, a unit for detecting signals on the direction-finding channel, a unit for tracking the object in the direction-finding channel, a block of statistical estimates of the initial bearing, the initial signal level, the initial magnitude of the change in bearing the initial value of the distance change, the software implementation block of Kalman filters, the unit for estimating the coordinates and elements of the object’s movement, the block in information output to the screen and information output unit to user banks, characterized in that the complex includes a signal detection unit for an elevation channel, an object tracking unit in an elevation channel, a unit for measuring the elevation angle to the object and signal levels from the object, a unit for calculating angle estimates the location and signal levels in the elevation channel and the unit for calculating the magnitude of the change in elevation angle, while the signals from the object received by the antenna are processed in the signal detection unit through the direction-finding channel and in the detection unit signals along the elevation channel for subsequent tracking of the object, respectively, in the tracking unit of the object in the bearing channel and in the tracking unit of the object in the elevating channel, then the signals from the tracking unit of the object in the bearing channel are sent to the block of statistical estimates of the initial bearing, the initial signal level, the initial change the bearing and the initial value of the distance change, and the signals from the object tracking unit in the goniometer channel to the unit for measuring the elevation angle to the object and the signal levels from the object, to the block for calculating estimates of elevation angle and signal levels in the elevation channel and to the unit for calculating estimates of magnitude of change in elevation angle, the computed estimates provide the construction of a variety of Kalman filters in the software implementation block of Kalman filters for subsequent obtaining in the estimator of coordinates and elements of the object’s motion current estimates of coordinates - distance, bearing and elevation and elements of the object’s movement - speed, course, magnitude of bearing change, magnitude of distance change and magnitude of angle m There, then the received data goes to the information output unit on the screen and to the information output unit in user banks to cover the current situation and make an operational decision.

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