CN111323769A - Airborne radar radio frequency stealth waveform selection method based on waveform library - Google Patents

Airborne radar radio frequency stealth waveform selection method based on waveform library Download PDF

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CN111323769A
CN111323769A CN202010138619.4A CN202010138619A CN111323769A CN 111323769 A CN111323769 A CN 111323769A CN 202010138619 A CN202010138619 A CN 202010138619A CN 111323769 A CN111323769 A CN 111323769A
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airborne radar
waveform
target
moment
time
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时晨光
王奕杰
丁琳涛
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Nanjing University of Aeronautics and Astronautics
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Nanjing University of Aeronautics and Astronautics
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/66—Radar-tracking systems; Analogous systems
    • G01S13/72—Radar-tracking systems; Analogous systems for two-dimensional tracking, e.g. combination of angle and range tracking, track-while-scan radar
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/28—Details of pulse systems
    • G01S7/282—Transmitters
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/35—Details of non-pulse systems
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/36—Means for anti-jamming, e.g. ECCM, i.e. electronic counter-counter measures

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  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Radar Systems Or Details Thereof (AREA)

Abstract

The invention discloses a method for selecting radio frequency stealth waveforms of an airborne radar based on a waveform library, which comprises the following steps: establishing an airborne radar transmitting waveform library; calculating a predicted target covariance matrix at the next moment; judging whether the airborne radar is started to irradiate and track the target at the next moment; defining an airborne radar waveform selection target function; establishing an airborne radar waveform selection model based on a waveform library; and solving the airborne radar waveform selection model based on the waveform library. The method not only improves the target tracking precision of the airborne radar, but also effectively controls the startup times of the airborne radar, thereby improving the radio frequency stealth performance of the airborne radar.

Description

Airborne radar radio frequency stealth waveform selection method based on waveform library
Technical Field
The invention relates to a radar signal processing technology, in particular to an airborne radar radio frequency stealth waveform selection method based on a waveform library.
Background
Traditional airborne radar transmits a fixed waveform to track a target, and radar measurement of the target depends on the transmitted waveform. Due to the immeasurability of the radar battle environment, the irradiation tracking of the target by adopting a single emission waveform is often difficult to achieve ideal tracking accuracy.
Radio frequency stealth radar is also called as low interception probability radar, and means that radar designers strive to seek a hidden or silent radar working mode, so that the radar is not intercepted by a passive interception receiver during working, and the aims of preventing the radar from being interfered or destroyed and improving the survival capability of the radar are fulfilled.
However, no airborne radar radio frequency stealth waveform selection method based on a waveform library exists in the prior art.
Disclosure of Invention
The purpose of the invention is as follows: in order to overcome the defects of the prior art, the invention provides a method for selecting the radio frequency stealth waveform of an airborne radar based on a waveform library.
The technical scheme is as follows: in order to realize the purpose, the invention adopts the following technical scheme:
a method for selecting airborne radar radio frequency stealth waveforms based on a waveform library comprises the following steps:
(1) establishing an airborne radar transmitting waveform library theta;
(2) calculating a predicted target covariance matrix at the next moment;
(3) judging whether the airborne radar is started to irradiate and track the target at the next moment;
(4) defining an airborne radar waveform selection target function;
(5) establishing an airborne radar waveform selection model based on a waveform library;
(6) and solving the airborne radar waveform selection model based on the waveform library.
Further, the airborne radar transmitting waveform library Θ in the step (1) comprises a triangular pulse signal, a gaussian modulation pulse signal, a chirp signal and a gaussian modulation chirp signal.
Further, tracking and filtering the single target by adopting an interactive multi-model extended Kalman filtering algorithm in the step (2), and predicting the target state at the k +1 moment at the k moment
Figure BDA0002398217790000011
Comprises the following steps:
Figure BDA0002398217790000021
wherein M is the total number of the target motion models,
Figure BDA0002398217790000022
the target state of model m at time k +1 is predicted for time k,
Figure BDA0002398217790000023
predicting the probability of the model m at the k +1 moment for the k moment; thus, a target covariance matrix for the predicted k +1 time at time k is obtained
Figure BDA0002398217790000024
Comprises the following steps:
Figure BDA0002398217790000025
wherein the content of the first and second substances,
Figure BDA0002398217790000026
a target covariance matrix of the model m at the moment k +1 is predicted for the moment k, and the superscript T represents the transposition operation of the matrix.
Further, in the step (3), if the k time predicts the target covariance matrix at the k +1 time
Figure BDA0002398217790000027
Is less than the preset target tracking error threshold ξ, i.e.:
Figure BDA0002398217790000028
the airborne radar is shut down at the moment k +1, and the passive sensor is adopted to cooperatively irradiate and track the target; acquiring a target measurement value at the k +1 moment, and returning to the step (2);
otherwise, the airborne radar is started to irradiate and track the target at the moment k +1, and the step (4) is executed.
Further, the on-board radar waveform selection target function defined in step (4) is as follows:
Figure BDA0002398217790000029
wherein WSOF represents the waveform selection target function, Tr [ ·, of the airborne radar]Denotes the trace operation of the matrix, Ωk+1Is the emission waveform of the airborne radar at the moment k +1,
Figure BDA00023982177900000210
the target covariance matrix at time k +1, i.e.:
Figure BDA00023982177900000211
wherein the content of the first and second substances,
Figure BDA00023982177900000212
the probability of model m at time k +1,
Figure BDA00023982177900000213
is the target covariance matrix for model m at time k +1,
Figure BDA00023982177900000214
the target state of model m at time k +1,
Figure BDA00023982177900000215
the target state at time k +1, namely:
Figure BDA00023982177900000216
further, when the airborne radar is started to irradiate and track the target at the time k +1 in the step (5), an airborne radar waveform selection model based on a waveform library is established, and the following steps are performed:
Figure BDA0002398217790000031
wherein, Tr [ ·]Denotes the trace operation of the matrix, Ωk+1Is the emission waveform of the airborne radar at the moment k +1,
Figure BDA0002398217790000032
and (2) representing a pre-established airborne radar transmitting waveform library by a target covariance matrix at the moment k + 1.
Further, in the step (6), an objective function is selected from a pre-established airborne radar transmission waveform library theta
Figure BDA0002398217790000033
The minimum waveform is used as the emission waveform of the airborne radar at the moment k +1, so that the whole airborne radar emission waveform self-adaptive selection process is completed; and (5) simultaneously, acquiring a target measurement value at the moment k +1, and returning to the step (2).
Has the advantages that: compared with the prior art, the invention has the following advantages:
(1) the main task of the method is to establish an airborne radar transmitting waveform library. Then, considering a battle scene that the airborne radar tracks a single target by adopting an interactive multi-model extended Kalman filtering algorithm, and judging whether the airborne radar is started to irradiate and track the target at the next moment according to the trace of the predicted target covariance matrix at the next moment and a preset target tracking error threshold value. If the target tracking error threshold value is met, the airborne radar is not started at the next moment, and the passive sensor tracks the target; if the preset target tracking error threshold value is not met, the next-time airborne radar is started to irradiate and track the target, an airborne radar waveform selection model based on a waveform library is established, the trace of the minimum target tracking error covariance matrix is taken as an optimization target, the given airborne radar emission waveform library is taken as a constraint condition, the next-time airborne radar emission waveform is subjected to self-adaptive optimization selection, and therefore the target tracking precision is improved, the starting times of the airborne radar are effectively reduced, and the purpose of improving the radio frequency stealth performance of the airborne radar is achieved.
The method has the advantages that the target tracking precision of the airborne radar is improved, the startup times of the airborne radar are effectively controlled, and the radio frequency stealth performance of the airborne radar is improved. The method adopts the airborne radar radio frequency stealth waveform selection method based on the waveform library, and judges whether the airborne radar is started to irradiate and track the target at the next moment according to the trace of the target covariance matrix predicted at the next moment and the preset target tracking error threshold. If the target tracking error threshold value is met, the airborne radar is not started at the next moment, and the passive sensor tracks the target; if the target tracking error threshold value is not met, the airborne radar is started to irradiate and track the target at the next moment, an airborne radar waveform selection model based on a waveform library is established, the trace of the minimum target tracking error covariance matrix is used as an optimization target, the given airborne radar emission waveform library is used as a constraint condition, and adaptive optimization selection is carried out on the airborne radar emission waveform at the next moment.
(2) Compared with the prior art, the airborne radar radio-frequency stealth waveform selection method based on the waveform library not only improves the target tracking precision of the airborne radar, but also effectively controls the startup times of the airborne radar, thereby improving the radio-frequency stealth performance of the airborne radar.
Drawings
Fig. 1 is a flow chart of an airborne radar radio frequency stealth waveform selection algorithm based on a waveform library.
Detailed Description
The structure and operation of the present invention will be further described with reference to the accompanying drawings.
The invention provides a method for selecting airborne radar radio frequency stealth waveforms based on a waveform library from actual engineering application. Then, considering a battle scene that the airborne radar tracks a single target by adopting an interactive multi-model extended Kalman filtering algorithm, and judging whether the airborne radar is started to irradiate and track the target at the next moment according to the track of the predicted target covariance matrix at the next moment obtained by calculation and a preset target tracking error threshold. If the target tracking error threshold value is met, the airborne radar is not started at the next moment, and the passive sensor tracks the target; if the preset target tracking error threshold value is not met, the next-time airborne radar is started to irradiate and track the target, at the moment, the waveform of the airborne radar is defined to select a target function, an airborne radar waveform selection model based on a waveform library is established, the trace of a minimum target tracking error covariance matrix is taken as an optimization target, the given airborne radar emission waveform library is taken as a constraint condition, the next-time airborne radar emission waveform is subjected to self-adaptive optimization selection, the target tracking precision is improved, meanwhile, the starting times of the airborne radar are effectively reduced, and the purpose of improving the radio frequency stealth performance of the airborne radar is achieved. Specifically, the method comprises the following steps:
as shown in fig. 1, a method for selecting an airborne radar radio-frequency stealth waveform based on a waveform library includes the following steps:
1. establishing an airborne radar transmitting waveform library;
the waveform library Θ includes radar waveforms such as a triangular pulse signal, a gaussian modulated pulse signal, a chirp signal, and a gaussian modulated chirp signal. And the transmitting waveforms of the airborne radar at the next moment are all selected from the waveform library.
2. Calculating a predicted target covariance matrix at the next moment;
the invention adopts an interactive multi-model extended Kalman filtering algorithm to track and filter a single target, so that the target state at the k +1 moment is predicted at the k moment
Figure BDA0002398217790000041
Comprises the following steps:
Figure BDA0002398217790000042
wherein M is the total number of the target motion models,
Figure BDA0002398217790000043
the target state of model m at time k +1 is predicted for time k,
Figure BDA0002398217790000051
the probability of model m at time k +1 is predicted for time k. Thus, a target covariance matrix for the predicted k +1 time at time k can be obtained
Figure BDA0002398217790000052
Comprises the following steps:
Figure BDA0002398217790000053
wherein the content of the first and second substances,
Figure BDA0002398217790000054
a target covariance matrix of the model m at the moment k +1 is predicted for the moment k, and the superscript T represents the transposition operation of the matrix.
3. Judging whether the airborne radar is started to irradiate and track the target at the next moment;
if the target covariance matrix at the k +1 moment is predicted at the k moment
Figure BDA0002398217790000055
Is less than the preset target tracking error threshold ξ, i.e.:
Figure BDA0002398217790000056
the airborne radar is shut down at the moment k +1, the passive sensor is adopted to cooperatively perform irradiation tracking on the target, a target measurement value at the moment k +1 is obtained, and then the step 2 is returned;
otherwise, the airborne radar is started to irradiate and track the target at the moment k +1, and the step 4 is executed.
4. Defining an airborne radar waveform selection target function;
defining an airborne radar waveform selection objective function as:
Figure BDA0002398217790000057
wherein, WSOF represents machineSelection of target function, Tr [. to carry radar waveform]Denotes the trace operation of the matrix, Ωk+1Is the emission waveform of the airborne radar at the moment k +1,
Figure BDA0002398217790000058
the target covariance matrix at time k +1, i.e.:
Figure BDA0002398217790000059
wherein the content of the first and second substances,
Figure BDA00023982177900000510
the probability of model m at time k +1,
Figure BDA00023982177900000511
is the target covariance matrix for model m at time k +1,
Figure BDA00023982177900000512
the target state of model m at time k +1,
Figure BDA00023982177900000513
the target state at time k +1, namely:
Figure BDA00023982177900000514
5. establishing an airborne radar waveform selection model based on a waveform library;
when the airborne radar is started to irradiate and track a target at the moment of k +1, establishing an airborne radar waveform selection model based on a waveform library, wherein the model is as follows:
Figure BDA0002398217790000061
wherein, Θ represents a pre-established airborne radar transmitting waveform library.
6. Solving an airborne radar waveform selection model based on a waveform library:
from pre-establishmentSelecting a target function from a transmitting waveform library theta of the airborne radar
Figure BDA0002398217790000062
And the minimum waveform is used as the emission waveform of the airborne radar at the moment k +1, so that the whole airborne radar emission waveform self-adaptive selection process is completed.
And meanwhile, acquiring a target measurement value at the moment k +1, and returning to the step 2.
The working principle and the working process of the invention are as follows:
the method firstly establishes an airborne radar transmitting waveform library theta. Then, considering an operation scene that the airborne radar tracks a single target by adopting an interactive multi-model extended Kalman filtering algorithm, and predicting a target covariance matrix at the k +1 moment according to the k moment
Figure BDA0002398217790000063
Judging whether the airborne radar is started to perform irradiation tracking on the target at the moment k +1 with a preset target tracking error threshold; traces using a k +1 time target covariance matrix
Figure BDA0002398217790000064
Selecting a target function as an airborne radar waveform; predicting the trace of the target covariance matrix according to the calculated next moment
Figure BDA0002398217790000065
Judging whether the airborne radar is started to irradiate and track the target at the next moment or not according to a preset target tracking error threshold value ξ, if the preset target tracking error threshold value is met, the airborne radar is not started at the next moment, the passive sensor tracks the target, and if the preset target tracking error threshold value is not met, the airborne radar is started to irradiate and track the target at the next moment
Figure BDA0002398217790000066
And establishing an airborne radar waveform selection model based on a waveform library to minimize target tracking errorsThe trace of the difference covariance matrix is taken as an optimization target, a given airborne radar transmitting waveform library is taken as a constraint condition, and a target function is selected from a pre-established airborne radar transmitting waveform library
Figure BDA0002398217790000067
And the minimum waveform is used as the emission waveform of the airborne radar at the next moment, so that the whole airborne radar emission waveform self-adaptive selection process is completed.

Claims (7)

1. A method for selecting airborne radar radio frequency stealth waveforms based on a waveform library is characterized by comprising the following steps:
(1) establishing an airborne radar transmitting waveform library theta;
(2) calculating a predicted target covariance matrix at the next moment;
(3) judging whether the airborne radar is started to irradiate and track the target at the next moment;
(4) defining an airborne radar waveform selection target function;
(5) establishing an airborne radar waveform selection model based on a waveform library;
(6) and solving the airborne radar waveform selection model based on the waveform library.
2. The method for selecting the radio-frequency stealth waveform of the airborne radar based on the waveform library according to claim 1, wherein the transmitted waveform library Θ of the airborne radar in the step (1) includes a triangular pulse signal, a gaussian modulated pulse signal, a chirp signal and a gaussian modulated chirp signal.
3. The method for selecting the airborne radar radio-frequency stealth waveform based on the waveform library according to claim 1, wherein in the step (2), tracking filtering is performed on a single target by adopting an interactive multi-model extended Kalman filtering algorithm, so that the target state at the k +1 moment is predicted at the k moment
Figure FDA0002398217780000011
Comprises the following steps:
Figure FDA0002398217780000012
wherein M is the total number of the target motion models,
Figure FDA0002398217780000013
the target state of model m at time k +1 is predicted for time k,
Figure FDA0002398217780000014
predicting the probability of the model m at the k +1 moment for the k moment; thus, a target covariance matrix for the predicted k +1 time at time k is obtained
Figure FDA0002398217780000015
Comprises the following steps:
Figure FDA0002398217780000016
wherein the content of the first and second substances,
Figure FDA0002398217780000017
a target covariance matrix of the model m at the moment k +1 is predicted for the moment k, and the superscript T represents the transposition operation of the matrix.
4. The method for selecting airborne radar radio frequency stealth waveforms based on the waveform library according to claim 1, wherein in the step (3), if the k time is predicted to be the k +1 time, the target covariance matrix is predicted
Figure FDA0002398217780000018
Is less than the preset target tracking error threshold ξ, i.e.:
Figure FDA0002398217780000019
the airborne radar is shut down at the moment k +1, and the passive sensor is adopted to cooperatively irradiate and track the target; acquiring a target measurement value at the k +1 moment, and returning to the step (2);
otherwise, the airborne radar is started to irradiate and track the target at the moment k +1, and the step (4) is executed.
5. The method for selecting the airborne radar radio-frequency stealth waveform based on the waveform library according to claim 1, wherein the airborne radar waveform selection target function defined in the step (4) is as follows:
Figure FDA0002398217780000021
wherein WSOF represents the waveform selection target function, Tr [ ·, of the airborne radar]Denotes the trace operation of the matrix, Ωk+1Is the emission waveform of the airborne radar at the moment k +1,
Figure FDA0002398217780000022
the target covariance matrix at time k +1, i.e.:
Figure FDA0002398217780000023
wherein the content of the first and second substances,
Figure FDA0002398217780000024
the probability of model m at time k +1,
Figure FDA0002398217780000025
is the target covariance matrix for model m at time k +1,
Figure FDA0002398217780000026
the target state of model m at time k +1,
Figure FDA0002398217780000027
the target state at time k +1, namely:
Figure FDA0002398217780000028
6. the method for selecting the airborne radar radio-frequency stealth waveform based on the waveform library according to claim 1, wherein in the step (5), when the airborne radar is powered on to perform irradiation tracking on the target at the time k +1, an airborne radar waveform selection model based on the waveform library is established as follows:
Figure FDA0002398217780000029
wherein WSOF represents the waveform selection target function, Tr [ ·, of the airborne radar]Denotes the trace operation of the matrix, Ωk+1Is the emission waveform of the airborne radar at the moment k +1,
Figure FDA00023982177800000210
and (2) representing a pre-established airborne radar transmitting waveform library by a target covariance matrix at the moment k + 1.
7. The method for selecting radio-frequency stealth waveforms of airborne radar based on waveform library according to claim 1, wherein in step (6), the objective function is selected from a pre-established airborne radar transmission waveform library Θ
Figure FDA00023982177800000211
The minimum waveform is used as the emission waveform of the airborne radar at the moment k +1, so that the whole airborne radar emission waveform self-adaptive selection process is completed; and (5) simultaneously, acquiring a target measurement value at the moment k +1, and returning to the step (2).
CN202010138619.4A 2020-03-03 2020-03-03 Airborne radar radio frequency stealth waveform selection method based on waveform library Pending CN111323769A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117169818A (en) * 2023-10-30 2023-12-05 哈尔滨工业大学（威海） Radar waveform design method for sea surface maneuvering target tracking

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20060165811A1 (en) * 2005-01-26 2006-07-27 Black Michael J Method and system for automatic decoding of motor cortical activity
CN106021697A (en) * 2016-05-17 2016-10-12 电子科技大学 Quick phased array radar time-energy resource combined management method
CN106461757A (en) * 2014-06-11 2017-02-22 古野电气株式会社 Radar device and transmission-signal control method

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20060165811A1 (en) * 2005-01-26 2006-07-27 Black Michael J Method and system for automatic decoding of motor cortical activity
CN106461757A (en) * 2014-06-11 2017-02-22 古野电气株式会社 Radar device and transmission-signal control method
CN106021697A (en) * 2016-05-17 2016-10-12 电子科技大学 Quick phased array radar time-energy resource combined management method

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
俞道滨等: "基于波形库的目标跟踪波形选择方法研究", 《雷达与对抗》 *
戴春亮等: "基于无源传感器协同的机载雷达自适应辐射控制算法", 《数据采集与处理》 *
时晨光: "机载雷达组网射频隐身技术研究", 《中国优秀博硕士学位论文全文数据库（博士） 信息科技辑》 *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117169818A (en) * 2023-10-30 2023-12-05 哈尔滨工业大学（威海） Radar waveform design method for sea surface maneuvering target tracking
CN117169818B (en) * 2023-10-30 2024-02-13 哈尔滨工业大学（威海） Radar waveform design method for sea surface maneuvering target tracking

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Application publication date: 20200623