Method for estimating the distance to an object, associated computer, system and carrier

Abstract

The present invention relates to a method for estimating the distance to an object (14), the estimating method being implemented by a computer (18) and comprising the steps of: - obtaining measurements of angular-velocity parameters of the object (14) and measurements of angular orientations of the object (14) with respect to a sensor (16), in order to obtain a plurality of sets of measurements, and - estimating the distance to the object (14) by applying an estimator to each set of measurements, the estimator assuming a movement of the object (14).

Description

[0001] DESCRIPTION

[0002] TITLE: Method for estimating the distance to an object, associated calculator, system and carrier

[0003] The present invention relates to a method for estimating the distance to an object. The present invention also relates to a computer capable of implementing the estimation method as well as to a system and a carrier comprising such a computer.

[0004] In the field of passive distance estimation between a carrier and an object, optronic equipment is used, particularly airborne, to determine the distance without active telemetry requiring laser or radar emission. Laser telemetry can in fact be limited by its range or by its lack of discretion, as the laser emission can be detected by the targeted object.

[0005] For this, it is known to use an estimator which is a Kalman filter applied to angular orientation measurements giving two angles under which the object is seen by a passive sensor. Such a technique is often referred to as a TPA technique, that is to say a passive trajectography technique by angle measurement.

[0006] Such a Kalman filter can be expressed in a Cartesian frame (relative or absolute) or in a spherical frame or in a hybrid form by alternating between the two types of frames according to the phases of the Kalman filter (typically a prediction phase in Cartesian and a correction phase in spherical).

[0007] In the general case, this problem of passive distance estimation from angular measurement is known to be "unobservable" in the sense that it is not soluble. To make this problem soluble, it is appropriate: to make an assumption about the trajectory of the observed object (a uniform rectilinear movement, a uniform circular movement, etc.) that the carrier performs a maneuver that will make the desired distance "observable".

[0008] However, for the estimate to converge and be accurate, the object should follow the assumed motion, which is most often a uniform rectilinear motion, for a sufficient duration to achieve good convergence. This duration can be difficult to achieve in practice due to the object's movements.

[0009] There is a need for a method for estimating the distance to an object, in particular a carrier, which is as fast as possible in order to relax this hypothesis on the validity duration of the trajectory of the targeted object. To this end, the description describes a method for estimating the distance to an object, in particular a carrier, the estimation method being implemented by a computer and comprising the steps of:

[0010] - obtaining measurements of angular velocity parameters of the object and measurements of angular orientations of the object relative to a sensor, to obtain a plurality of sets of measurements, and

[0011] - estimation of the distance to the object by applying an estimator to each set of measurements, the estimator assuming movement of the object.

[0012] According to particular embodiments, the estimation method has one or more of the following characteristics, taken in isolation or in all technically possible combinations:

[0013] - each angular velocity parameter is the angular velocity measured by the sensor.

[0014] - the sensor carrying out the angular orientation measurements is part of a platform whose line of sight is stabilized by an angular speed setpoint, each angular speed parameter is the angular speed setpoint.

[0015] - the sensor comprises a sensor block and a processing block, the processing block comprising a plurality of sub-blocks, the measurements of angular velocity parameters of the object and of angular orientation measurements being obtained by obtaining the output of a respective sub-block of the processing block of the sensor.

[0016] - during the obtaining step, measurements of the acceleration of the object are also obtained, each set of measurements comprising at least one acceleration measurement.

[0017] - the sensor carrying out the angular orientation measurements includes an inertial unit.

[0018] - the sensor carrying out the angular orientation measurements includes gyrometers.

[0019] - the estimator is a Kalman filter.

[0020] The description also describes a calculator suitable for estimating the distance to an object, the calculator being suitable for:

[0021] - obtaining measurements of angular velocity parameters of the object and measurements of angular orientations of the object relative to a sensor, to obtain a plurality of sets of measurements, and

[0022] - estimating the distance to the object by applying an estimator to each set of measurements, the estimator assuming movement of the object. The description also proposes a system for estimating the distance to an object, in particular a carrier, the estimation system comprising:

[0023] - a first sensor capable of measuring an angular velocity parameter of the object,

[0024] - a second sensor capable of measuring the angular orientations of the object relative to the second sensor, and

[0025] - a calculator as previously described, the calculator being capable of obtaining each angular velocity parameter and the angular orientations by receiving the measurements from each of the sensors.

[0026] According to a particular embodiment, the first sensor and the second sensor are combined.

[0027] The description also describes a carrier comprising a calculator as previously described or an estimation system as previously described.

[0028] In this description, the expression "suitable for" means indifferently "adapted for", "adapted to" or "configured for".

[0029] Characteristics and advantages of the invention will appear on reading the description which follows, given solely by way of non-limiting example, and made with reference to the appended drawings, in which:

[0030] - [Fig 1] Figure 1 is a schematic representation of a carrier equipped with a system for estimating the distance to an object,

[0031] - [Fig 2] Figure 2 is a block diagram representation of the components of an example estimation system according to Figure 1, and

[0032] - [Fig 3] Figure 3 is a flowchart of an example implementation of a method for estimating the distance to an object.

[0033] A carrier 10 is shown schematically in Figure 1.

[0034] The carrier 10 shown is, for example, an airplane.

[0035] Alternatively, the carrier 10 is any type of aircraft such as a helicopter or a missile.

[0036] It is also possible to consider here a carrier which is a land or naval vehicle.

[0037] The carrier 10 comprises a system 12 for estimating the distance to an object.

[0038] The estimation system 12 thus seeks to obtain in real time the distance between the targeted object, which may be another carrier called the observed carrier 14, and the estimation system 12.

[0039] The observed carrier 14 is here represented by a square to symbolize the fact that the observed carrier 14 is, in this context, generally very far from the carrier 10, typically several tens of kilometers. The estimation system 12 can be seen as optronic equipment of the carrier 10.

[0040] These include equipment with a steerable line of sight and a target tracking function such as a designation pod, an optronic ball or an infrared search and track device. The latter equipment is more often referred to as IRST equipment, the abbreviation IRST referring to the English term "InfraRed Seach and Track".

[0041] The estimation system 12 comprises a sensor 16 and a computer 18.

[0042] The sensor 16 is for example a passive optronic sensor, that is to say capable of measuring quantities without the sensor 16 having to emit a signal.

[0043] The sensor 16 is capable of obtaining measurements of angular parameters of a target distant from the sensor 16, relative to the sensor 16.

[0044] According to the example described, the sensor 16 tracks the observed carrier 14 and is capable of measuring two angular orientations of the observed carrier 14 in a fixed reference frame.

[0045] Typically, sensor 16 gives two angular values ​​which are <p l’azimut et 6 l’élévation.

[0046] Both orientations are defined in the local geographic reference frame, i.e. a reference frame centered on the sensor 16 with a first x axis corresponding to north, a second y axis corresponding to east and a third z axis corresponding to bottom.

[0047] More specifically, azimuth is the rotation around the third z-axis which is positive in the north-east direction while elevation is the rotation around a fourth y'-axis, the fourth y'-axis being deduced from the second y-axis by the azimuth rotation. Elevation is, moreover, chosen to be positive upwards.

[0048] The sensor 16 thus provides at each instant a pair of angular orientations of the observed carrier 14.

[0049] The sensor 16 is also capable of providing the angular velocity of the orientation to the observed carrier 14.

[0050] According to a particular example, the sensor 16 includes an inertial unit.

[0051] As seen in the example of Figure 2, the inertial unit comprises a sensor block 20 and a processing block 22.

[0052] The sensor block 20 comprises gyrometers 24 and accelerometers 26.

[0053] The gyrometers 24 provide the angular velocity of the observed carrier 14 while the accelerometers 26 provide the acceleration of the carrier 10.

[0054] The processing block 22 is capable of receiving the measurements from the gyrometers 24 and the measurements from the accelerometers 26 and of processing the measurements received to obtain the position, the speed of the carrier 10 and the attitude (angular orientations) and the angular speed of the observed carrier 14.

[0055] The processing block 22 comprises several sub-blocks: a first correction sub-block 28, a second correction sub-block 30, a first integration sub-block 32, a second integration sub-block 34 and a third integration sub-block 36.

[0056] The first correction sub-block 28 receives the measurements from the gyrometers 24 and is capable of applying a correction to the measurements received.

[0057] According to the proposed example, the first correction sub-block 28 corrects the effect of the Earth's rotation on the received angular velocity measurements.

[0058] The correction applied by the first sub-block also includes compensation for the rotation speed of the rotation trihedron relative to the Earth.

[0059] The first correction sub-block 28 thus outputs the angular velocity of the observed carrier 14 by correction of the raw measurements of the gyrometer 24.

[0060] The first integration sub-block 32 receives as input the angular velocity thus obtained and integrates it over time to obtain angular measurements (attitude).

[0061] The second correction sub-block 30 receives the measurements from the accelerometers 26 and is capable of applying a correction to the measurements received.

[0062] According to the proposed example, the second correction sub-block 30 corrects the effect of the Earth's rotation on the received acceleration measurements.

[0063] The correction applied by the second correction sub-block 30 also includes gravity compensation.

[0064] The second correction sub-block 30 thus outputs the acceleration of the carrier 10 by correcting the raw measurements of the accelerometers 26.

[0065] The second integration sub-block 34 receives as input the acceleration thus obtained and integrates it over time to obtain the speed of the carrier 10 and the correction sub-block 30 further receives the speed of the second integration sub-block 34.

[0066] The third integration sub-block 36 receives as input the speed calculated by the second integration sub-block 34 and integrates it in time to obtain the position of the observed carrier 14.

[0067] In the proposed example, the corrections to be applied are obtained using other calculated values.

[0068] More specifically, each correction sub-block receives the position of the third integration sub-block 36 and the angular measurements of the first integration sub-block 32.

[0069] The calculator 18 is an electronic circuit designed to manipulate and / or transform data represented by electronic or physical quantities in registers of the calculator and / or memories into other similar data corresponding to physical data in the memories of registers or other types of display devices, transmission devices or storage devices.

[0070] As specific examples, the calculator 18 is produced in the form of a programmable logic component, such as an FPGA (Field Programmable Gate Array), or an integrated circuit, such as an ASIC (Application Specific Integrated Circuit) or in the form of a processor programmable using a computer language.

[0071] The calculator 18 is capable of implementing an estimator on measurements from the sensor 16 to estimate the distance to the observed carrier 14.

[0072] As seen in Figure 2, the computer 18 implements a Kalman filter which comprises a state prediction unit 38, a first extraction unit 40, a second extraction unit 42, correction unit 48, a first subtractor 44, a second subtractor 46, a correction unit 48, and an adder 49.

[0073] The state prediction unit 38 receives the velocity and position of the observed carrier 14 and predicts the state.

[0074] The first extraction unit 40 obtains an angular velocity prediction from the predicted state.

[0075] The first subtractor 44 is connected to the output of the first correction sub-block 28 of the sensor 16 and thus receives the measured angular velocity of the observed carrier 14.

[0076] The first subtractor 44 is also connected to the output of the first extraction unit 40 and thus receives an angular velocity prediction.

[0077] The first subtractor 44 is thus capable of performing the subtraction between the measured angular velocity and the predicted angular velocity.

[0078] The result of such subtraction is an angular velocity correction which is sent to the correction unit 48.

[0079] The second extraction unit 42 obtains an angular orientation prediction from the predicted state.

[0080] The second subtractor 46 is connected to the output of the first integration sub-block 32 of the sensor 16 and thus receives the measured angular orientation of the observed carrier 14.

[0081] The second subtractor 46 is also connected to the output of the second extraction unit 42 and thus receives an angular orientation prediction.

[0082] The second subtractor 46 is thus capable of performing the subtraction between the measured angular orientation and the predicted angular orientation.

[0083] The result of such a subtraction is an angular orientation correction which is sent to the correction unit 48. The correction unit 48 is capable of receiving the angular velocity correction obtained by the first subtractor 44 and the angular orientation correction of the second subtractor 46 and of converting these corrections into a correction of the predicted state.

[0084] The adder 49 receives the correction of the predicted state from the correction unit 48 to which it is connected.

[0085] Adder 49 is also connected to the prediction block and thus adds the correction to the state predicted by the prediction block.

[0086] The adder 49 thus obtains a corrected predicted state which gives the estimate of the position and speed of the observed carrier 14.

[0087] The estimation of the position of the observed carrier 14 corresponds to an estimation of the distance since the position of the estimation system 12 is known.

[0088] The calculator 18 is thus capable of implementing a method for estimating the distance to the observed carrier 14.

[0089] An example of operation of the calculator 18 is now described with reference to FIG. 3 which illustrates a flowchart of an example of implementation of the estimation method.

[0090] The estimation process includes a step of obtaining E50 and a determination step.

[0091] The estimation method aims to estimate the distance to the observed carrier 14, that is to say to give the distance between the estimation system 12 and the observed carrier 14.

[0092] According to the example described, the estimation method comprises an obtaining step E50 and an estimation step E52.

[0093] During the obtaining step E50, measurements of the angular speed of the observed carrier 14 are obtained by the computer 18 as well as measurements of angular orientations.

[0094] As seen in Figure 2, the computer 18 obtains the measurement of the angular velocity from the output of the first correction sub-block 28 and the measurement of angular orientations from the output of the first integration sub-block 32.

[0095] The calculator 18 thus obtains a set of measurements for each instant.

[0096] During the estimation step E52, the calculator 18 applies a Kalman filter to each set of measurements to obtain an estimate of the distance (or position) of the observed carrier 14.

[0097] According to the example described, the estimator is a Kalman filter which has both angular measurements (attitudes) and angular velocity measurements.

[0098] The Kalman filter allows us to predict a state vector X written in modified spherical coordinates:

[0099] Or :

[0100] • x4, ... , x6 designate the six coordinates of the vector X,

[0101] • r is the distance,

[0102] • 0 elevation,

[0103] • <p I’azimut,

[0104] • f the radial velocity,

[0105] • 0 the angular velocity in elevation, and

[0106] • <p la vitesse angulaire en azimut.

[0107] Such a technique of applying a Kalman filter in modified spherical coordinates is often referred to by the acronym MSC-KF, which refers to the corresponding English name of "Modified Spherical Coordinate Kalman Filter".

[0108] In these notations, the set of measurements available to the calculator 18 is a set of four measurements: angular measurements which are noted measure9e measure(fl and angular velocity measurements which are noted as measure^ and measure^ .

[0109] The prediction equations of the Kalman filter (corresponding to the hypothesis of uniform rectilinear motion of the observed carrier 14 expressed in a spherical frame) are written as follows:

[0110] Or :

[0111] • HAS x , HAS Y and A z denote the acceleration of the carrier 10, using here the notations used in “Angle Only Tracking Filter in Modified Spherical Coordinates” by D. Stallard, Journal of Guidance Control Dynamics, Vol 14, issue 3, May 1991.

[0112] The observation equations for calculating innovation (corresponding to the evolution of quantities) are written:

[0113] Or :

[0114] • innov Xi denotes the innovation of the component Xj of the state vector X,

[0115] • fi etÆ denote functions representing the possible change of reference frame necessary to express the angular velocity measurements in the frame in which the state vector is expressed.

[0116] Due to the availability of angular velocity measurements, the calculator 18 has 4 observation equations instead of the 2 observation equations provided by the angular positions.

[0117] This avoids the convergence time of the estimate of angular velocities from angular positions.

[0118] In simulations, the applicant thus obtained a gain of 20% on the convergence time of an estimator using angular speeds and angular measurements compared to the same estimator using only angular measurements. This gain was measured for a distance accuracy of 10%.

[0119] Such an acceleration of the convergence of the estimator reduces the duration during which the observed carrier 14 must respect the movement model used for the estimation, which makes it possible to extend the operational field of use of the passive distance estimation method.

[0120] A reduction in static bias is also expected since static biases do not impact speed measurements.

[0121] It may be noted that this improvement in convergence can be obtained for existing systems by very simply adapting the processing block 22 and the computer 18. In fact, the method here uses an intermediate output from the processing block 22.

[0122] Other embodiments benefiting from the preceding advantages are also conceivable.

[0123] Instead of using the angular velocity itself as the angular velocity parameter, in the presence of a platform whose line of sight is stabilized by an angular velocity setpoint, it is possible to obtain the angular velocity setpoint during the E50 obtaining step.

[0124] The platform is thus a gyro-stabilized platform whose stabilization instructions are used.

[0125] In fact, the stabilization instructions reflect at a current instant the angular speeds allowing the line of sight to be maintained on the observed carrier 14 while the measurements may be affected by the defects of the gyrometers 24.

[0126] Alternatively or in addition, during the step of obtaining E50, measurements of the acceleration of the object are also obtained, each set of measurements comprising at least one acceleration measurement.

[0127] Indeed, these acceleration measurements are available at the output of the second correction sub-block 30.

[0128] Under such an assumption, the state vector predicted by the estimator becomes a 9-component state vector instead of a 6-component one.

[0129] Furthermore, other estimators can be used in this method.

[0130] In particular, the Kalman filter relies on an assumption of uniform rectilinear motion but an estimator assuming uniform circular motion could be considered in this method.

[0131] From a hardware point of view, other sensors than an inertial unit are possible.

[0132] The sensor 16 may, for example, be devoid of an accelerometer 26, so that the sensor 16 then comprises gyrometers 24 and a processing block 22 reduced to the first correction sub-block 28 and the first integration sub-block 32.

[0133] It is also possible to have a first sensor measuring angular orientations and a second sensor measuring angular speeds.

[0134] The sensor 16 is here more generally an orientable optronic device having a means of measuring the angular attitude and the angular speed integral with the optronic line of sight.

[0135] Preferably, the sensor 16 is a passive sensor, that is to say that the sensor 16 does not emit any pulses to the environment.

[0136] Thus, in a general case, the system 12 for estimating the distance to the observed carrier 14 comprises a first sensor capable of measuring an angular velocity parameter of the object and a second sensor capable of measuring the angular orientations of the object relative to the second sensor, the computer 18 receiving the measurements from each of the sensors. The first sensor and the second sensor are, depending on the embodiments, two different sensors or one and the same sensor.

Claims

CLAIMS 1. Method for estimating the distance to an object, in particular a carrier (14), the estimation method being implemented by a computer (18) and comprising the steps of: - obtaining measurements of angular velocity parameters of the object and measurements of angular orientations of the object relative to a sensor (16), to obtain a plurality of sets of measurements, and - estimation of the distance to the object by applying an estimator to each set of measurements, the estimator assuming movement of the object.

2. Estimation method according to claim 1, in which each angular velocity parameter is the angular velocity measured by the sensor (16).

3. Estimation method according to claim 1, in which the sensor (16) carrying out the angular orientation measurements is part of a platform whose line of sight is stabilized by an angular speed setpoint, each angular speed parameter is the angular speed setpoint.

4. Estimation method according to any one of claims 1 to 3, in which the sensor (16) comprises a sensor block (20) and a processing block (22), the processing block (22) comprising a plurality of sub-blocks, the measurements of angular velocity parameters of the object and of angular orientation measurements being obtained by obtaining the output of a respective sub-block of the processing block (22) of the sensor (16).

5. Estimation method according to any one of claims 1 to 4, in which, during the obtaining step, measurements of the acceleration of the object are also obtained, each set of measurements comprising at least one acceleration measurement.

6. Estimation method according to any one of claims 1 to 5, in which the sensor (16) carrying out the angular orientation measurements comprises an inertial unit.

7. Estimation method according to any one of claims 1 to 5, in which the sensor (16) carrying out the angular orientation measurements comprises gyrometers (24).

8. Estimation method according to any one of claims 1 to 7, in which the estimator is a Kalman filter.

9. Calculator (18) suitable for estimating the distance to an object, the calculator (18) being suitable for: - obtaining measurements of angular velocity parameters of the object and measurements of angular orientations of the object relative to a sensor (16), to obtain a plurality of sets of measurements, and - estimate the distance to the object by applying an estimator to each set of measurements, the estimator assuming movement of the object.

10. System for estimating (12) the distance to an object, in particular a carrier (14), the estimation system (12) comprising: - a first sensor capable of measuring an angular velocity parameter of the object, - a second sensor capable of measuring the angular orientations of the object relative to the second sensor, and - a calculator (18) according to claim 9, the calculator (18) being capable of obtaining each angular speed parameter and the angular orientations by receiving the measurements from each of the sensors.

11. Estimation system according to claim 10, wherein the first sensor and the second sensor are the same.

12. Carrier (10) comprising a calculator (18) according to claim 9 or an estimation system (12) according to claim 10 or 11.

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