CN114839600A - High-precision radar level measurement and control system - Google Patents

High-precision radar level measurement and control system Download PDF

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CN114839600A
CN114839600A CN202210258381.8A CN202210258381A CN114839600A CN 114839600 A CN114839600 A CN 114839600A CN 202210258381 A CN202210258381 A CN 202210258381A CN 114839600 A CN114839600 A CN 114839600A
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module
data
radar
reflected wave
frequency signal
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王志富
牛国良
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Hebei Huachuang Measurement And Control Technology Co ltd
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Hebei Huachuang Measurement And Control Technology Co ltd
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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
    • 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
    • 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
    • G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
    • G01S13/06—Systems determining position data of a target
    • 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
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/93—Radar or analogous systems specially adapted for specific applications for anti-collision purposes
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
    • Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

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  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
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Abstract

The invention discloses a high-precision radar level measurement and control system which comprises a signal receiving and reflecting module, an antenna module, a data algorithm module, an analog-to-digital conversion module, a high-frequency signal processing module, a touch screen display module and a power supply module, wherein the signal receiving and reflecting module is used for receiving and reflecting a signal; the analog-to-digital conversion module is connected with the signal receiving and reflecting module, the high-frequency signal processing module and the touch screen display module, and is used for mutually converting an analog signal and a digital signal, and the high-frequency signal processing module is simultaneously connected with the antenna module; the signal receiving and reflecting module receives the signal collected by the antenna module, and the signal is transmitted after being processed by the data algorithm module; the touch screen display module is used for setting and adjusting data parameters of the system; the high-frequency signal processing module is used for generating and processing a high-frequency signal; the power supply module respectively supplies power to the analog-to-digital conversion module, the high-frequency signal processing module and the signal receiving and reflecting module, the system can accurately and intelligently track the target, and has high anti-interference performance, reliability and precision.

Description

High-precision radar level measurement and control system
Technical Field
The invention relates to the field of radars, in particular to a high-precision radar level measurement and control system.
Background
The high-precision radar is mainly used for detecting the position of an object and is an active remote sensing device. The high-altitude wind-measuring radar commonly used together with a radiosonde has the function of positioning a displacement balloon and cannot be called as a high-precision radar. Most radar installations are composed of an antenna and associated controller, transmitter, receiver, computer, etc. main parts. The antenna is an indispensable component for processing signals generated by a high-precision radar system, is mainly responsible for transmitting and receiving radar signals, and needs to move to cooperate with monitoring in order to detect a target. Therefore, the method plays an important role in controlling the high-precision radar antenna.
Radar countermeasure reconnaissance is an indispensable important link in the field of information countermeasure, and plays an increasingly important role in mastering battlefield initiative. However, with the increasingly complex electromagnetic environment, new system radars are gradually dominant, information reconnaissance based on a single sensor no longer has wide adaptability, and a high-precision algorithm is fused into the processing of radar reflected wave data to serve as a processing means for comprehensively analyzing intercepted information of different data, so that the method has more accurate and stable working performance compared with the single sensor.
Disclosure of Invention
In order to overcome the defects and shortcomings in the prior art, the invention provides the high-precision radar level measurement and control system, the system adopts a single chip microcomputer development system, the system requirements can be met, the cost is reduced, the high-precision radar control system can accurately and intelligently work, the system works stably, and the reliability is higher.
The technical scheme adopted by the invention is that the system comprises a signal receiving and reflecting module, an antenna module, a data algorithm module, an analog-to-digital conversion module, a high-frequency signal processing module, a touch screen display module and a power supply module;
the analog-to-digital conversion module is connected with the signal receiving and reflecting module, the high-frequency signal processing module and the touch screen display module, and is used for mutually converting an analog signal and a digital signal, and the high-frequency signal processing module is simultaneously connected with the antenna module;
the signal receiving and reflecting module receives signals collected by the antenna module, and the signals are processed by the data algorithm module and then transmitted out;
the touch screen display module is used for setting and adjusting data parameters of the system;
the high-frequency signal processing module is used for generating and processing a high-frequency signal;
and the power supply module is used for respectively supplying power to the analog-to-digital conversion module, the high-frequency signal processing module and the signal receiving and reflecting module.
Furthermore, the antenna module sends a control instruction by using a local computer, and transmits the control instruction to the high-frequency signal processing module through a serial communication bus RS-232, and the high-frequency signal processing module receives the control instruction of the upper computer and sends a corresponding effective signal to a driver of a corresponding motor to generate and process a high-frequency signal according to requirements.
Furthermore, the development of the circuit board part of the high-frequency signal processing module is mainly completed by the development of a single chip microcomputer, and the model of the single chip microcomputer is AT89S 52.
Furthermore, the single chip microcomputer is used for finishing the signal processing of the control motor and the digital converter of the rotary transformer.
Further, after the system starts working, the data algorithm module enters the program, when the program is entered, firstly, the system can complete all initializations needing configuration, secondly, the instruction zone bit is continuously judged, and when the zone bit changes, the main function can call a certain subprogram.
Further, the data algorithm module processes the signal data acquired by the antenna module according to the following steps:
step S1: identifying radar reflected wave data, and removing collected abnormal data;
step S2: carrying out weight solving on the normal data;
step S3: and weighting the result after the weight solution to obtain interference-free radar data.
Further, in step S1, the outlier is removed by using a quartile method, and n data numbers of the radar reflection waves are sorted from small to large to obtain a group of detection sequences: d 1 ,D 2 ,…,D n Defining the quartile A on the test sequence c Is in the position N u (n +1)/4, lower quartile A b Is in the position N l 3(N +1)/4, N u Is e and the fractional part is f, then the expression of upper and lower quartiles:
Figure BDA0003549672090000031
and (3) obtaining the quartile dispersion:
d A ＝A c -A b 。
further, in the step S1, for all local expectations, data with an expectation value larger than the upper quartile by θ dA is defined as invalid data θ e [1,2 ∈]Is a threshold parameter, i.e. the interval for determining whether the data is valid is [ gamma ] 1 ,γ 2 ]：
Figure BDA0003549672090000041
Interval [ gamma ] 1 ,γ 2 ]The inner radar reflected wave data is considered to be valid data, interval [ gamma ] 1 ,γ 2 ]And the data of the external radar reflected waves are considered as abnormal data and are removed.
Further, in step S2, after removing the abnormal values, calculating corresponding weights of the radar reflected wave data, and determining the weights by using local expectation and variance, respectively, to obtain final integrated weights, for the local expectation, first, using a consistency measure operator based on an exponential decay function to solve a confidence distance between two expectations, where an operator expression is:
d ij ＝exp(-(x i -x j ) 2 )
d nm ＝exp(-(D n -D m ) 2 )
further obtaining a confidence distance matrix D n From d nm D is more than or equal to 0 nm ≤1，d nm The smaller the degree of support of the nth radar reflected wave data by the mth radar reflected wave data is, the higher the degree of support of the mth radar reflected wave data is, the smaller the degree of support of the mth radar reflected wave data by the nth radar reflected wave data is, the higher the degree of support of the mth radar reflected wave data by the nth radar reflected wave data by the mth radar is nm Size of (2)Giving a measure of the degree of support, order
s nm ＝1-d nm (n，m＝1，2，...，i)
s nm Representing local expectation D between two radar reflected wave data n And D m The mutual support degree between the data and the data is weighted by the support degree, and the sum G of the support matrix and the nth column of all the data of the radar reflected waves is calculated by the representation n The support degree of the nth radar reflected wave data is as follows:
Figure BDA0003549672090000042
obtaining radar reflected wave data weight H based on local expectation p Comprises the following steps:
Figure BDA0003549672090000043
determining variance weight and comprehensive weight, and obtaining the data weight H of each radar reflected wave by using a self-adaptive fusion algorithm for local variance A The method comprises the following steps:
Figure BDA0003549672090000051
further, in step S3, after the expected weight and the variance weight are obtained, the expected weight and the variance weight may be weighted averagely to obtain a comprehensive weight H:
Figure BDA0003549672090000052
and finally, weighting by using the comprehensive weight to obtain a fusion result of the radar reflected wave data.
The invention has the beneficial effects that: the system can complete corresponding functions according to the instruction information of the radar host, and the indexes required by the system are achieved. The target tracking is accurate and intelligent, the system works stably, and the system has strong anti-interference performance and reliability and high precision.
Drawings
FIG. 1 is an overall block diagram of the radar control system of the present invention;
FIG. 2 is a signal trace diagram of the antenna module of the present invention;
FIG. 3 is a block diagram of the high frequency signal processing of the present invention;
FIG. 4 is a signal control diagram of the present invention;
FIG. 5 is an algorithm flow diagram of the present invention.
Detailed Description
It should be noted that the embodiments and features of the embodiments can be combined with each other without conflict, and the present application will be further described in detail with reference to the drawings and specific embodiments.
As shown in fig. 1, a high-precision radar level measurement and control system includes a signal receiving and reflecting module, an antenna module, a data algorithm module, an analog-to-digital conversion module, a high-frequency signal processing module, a touch screen display module, and a power supply module;
the analog-to-digital conversion module is connected with the signal receiving and reflecting module, the high-frequency signal processing module and the touch screen display module, and is used for mutually converting an analog signal and a digital signal, and the high-frequency signal processing module is simultaneously connected with the antenna module;
the signal receiving and reflecting module receives signals collected by the antenna module, and the signals are processed by the data algorithm module and then transmitted out;
the touch screen display module is used for setting and adjusting data parameters of the system;
the high-frequency signal processing module is used for generating and processing a high-frequency signal;
and the power supply module is used for respectively supplying power to the analog-to-digital conversion module, the high-frequency signal processing module and the signal receiving and reflecting module.
The target tracking and positioning of the measurement and control radar is essentially a real-time tracking and filtering problem of a target state, and in brief, a target object is positioned through a fixed algorithm according to target measurement data obtained from a sensor according to needs. At present, the method is widely applied to military and civil fields, so that the target positioning and tracking must be reliable and accurate. In the field of national defense, the target tracking technology can be used for detecting the direction of enemy missiles, tracking enemy ships, monitoring the geographical positions of national special workers and the like. In civil use, target tracking and positioning are used for tracking unmanned self-vehicles, traffic control in cities, obstacle avoidance of robots and the like. Therefore, the measurement and control radar plays a very important role in target tracking and positioning in the life and production of the national people.
At present, the main research direction of scientific researchers in the aspect of radar measurement and control is focused on the tracking problem of a moving target. When the maneuvering target moves, parameters such as the flying speed, the flying direction, the flying arc radius and the like of the maneuvering target change at any time and any place, and a lot of interference from other objects exists in the moving process of the target, so that a more excellent radar tracking technology needs to be adopted, and the performance of a measurement and control radar is tested. The dynamic tracking and control of target objects are required to be realized in the military and civil fields from time to time, which requires high continuity of radar target tracking and high integrity of radar feedback data. In addition, requirements for rapid response of target capturing, multi-target tracking, data feedback processing, target capturing positioning methods and the like are increasing. The measurement and control radar applied to the military field also has the capability of detecting a small radar scattering cross section target such as a stealth aircraft.
At present, the international application of the ultra-high performance multi-core computer to the measurement and control radar mainly comprises 4 technologies, namely (1) the application of the ultra-high performance multi-core computer to the detection of the target to be captured basically realizes the automation and the intellectualization of the measurement and control radar, and the demand of technical personnel and operating personnel is reduced, so that the measurement and control radar becomes an unattended state. (2) The adoption of advanced transceiver makes the monitored data very reliable, and equipment maintenance and change are convenient. (3) In the aspect of reliability, the measurement and control radar has a more perfect and self-adaptive self-learning automatic fault detection function. (4) The measurement and control radar system and the satellite relay communication system are matched for use, so that the anti-interference performance and the automation level of the radar are obviously improved, and other interference signals can be shielded, and monitoring, interception, interference and other people damage by an enemy can be prevented.
As shown in fig. 2, the antenna module sends a control command by using a local computer, and transmits the control command to the high-frequency signal processing module through a serial communication bus RS-232, and the high-frequency signal processing module receives the control command of the upper computer and sends a corresponding effective signal to a driver of a corresponding motor to generate and process a high-frequency signal according to the requirement.
When a plurality of targets are captured, perhaps several targets are moving, so that tracking must be performed from time to time by using a tracking algorithm for maneuvering detection. The multi-target tracking technology has wide application, such as defense of enemy missiles, sea, land and air detection, air traffic order combing and the like.
The detection means uses an averaging method, and once the maneuver information is detected, the filter uses higher-dimensional state measurements to which new state quantities are attached, based on which a new model is calculated. Then the non-maneuvering detector detects the elimination of the maneuvering and switches to the original model. The algorithm only focuses on the current dynamic state of the target, and the obtained positioning information has no relation with the past state, so that the algorithm has better performance on dynamic target monitoring.
As shown in fig. 3, the development of the high-frequency signal processing module circuit board part is mainly completed by the development of a single chip microcomputer, and the model of the single chip microcomputer is AT89S 52.
The single chip is used for controlling the signal processing of the motor and a digital converter of the rotary transformer.
The basic idea of the tracking algorithm of maneuver detection is that the model which is established by us originally is changed when the maneuver occurs, so that the pre-estimated value of the target state deviates from the inherent state, and the filtering residual characteristic changes. Therefore, a technician can predict whether the target is maneuvering or maneuvering ending by observing the residual change of the target movement, and based on the observation, the technician can further adjust the tracking algorithm, namely perform noise variance time adjustment or model time-to-time conversion, and adjust the structure of the filter gain and the filter according to a certain algorithm so as to realize better tracking of the target.
Modern radars use digital computers to perform data processing operations. The motion parameters such as specific position, speed, acceleration and the like of a target of a radar measured value can be comprehensively estimated by using a parameter estimation technology; forming various data information about the target object; the expected position of the target object, the attack target, the color state, and the next-state are estimated. The data processing steps of the measurement and control radar are divided into five parts, namely 1, data formatting, 2, data correction, 3, coordinate transformation, 4, tracking filter processing, 5 and target track processing.
The measuring and controlling radar detects a large amount of analog quantity in a data form, but a computer can only process digital quantity, so that the analog quantity can enter the computer after being processed by a receiving system. The radar pair measures, the measured data is stored in a systematic format, the measured data is firstly programmed into a plurality of units, and each unit can only receive the measured data at a fixed time point. The radar data words are used as data, namely original quantities of a unified system are numbered and then sent to a fixed storage position in a computer memory.
As shown in fig. 4, after the system starts working, the data algorithm module enters the program, and when the program enters the program, firstly, the system completes all initializations that need to be configured, secondly, the instruction flag bit is continuously judged, and when the flag bit changes, the main function calls a certain subprogram.
The mathematical theory mainly used for data correction is the unbiased estimation and interpolation compensation correction of the data. In order to ensure that the data measured by the measurement and control radar is accurate, a batch of correction compensation auxiliary data needs to be stored in a computer in advance. When the radar works, a storage address of a correction value is searched according to measured data, and finally, the measured value of the measurement and control radar is corrected and compensated by an interpolation method, so that the accuracy of the data can be realized.
It is well known that in mathematical calculations, if the equation of motion of the object is extremely complex, it can be simplified by selecting a suitable coordinate system and facilitates further computational processing of the data. The radar measurement data link mainly depends on and the essential equipment is an antenna. The measurement is based on the spherical coordinate system, such as the azimuth, the distance, the state and the like. Sometimes, to simplify the calculation, we need to convert the data in the spherical coordinates into a rectangular coordinate system, which is also our preferred coordinate system. For example, the acceleration of the target object observed in a spherical coordinate system has a composition with geometric components that cannot represent the motion characteristics of the target in the inertial space. If the data processing is also performed in the radar spherical coordinate system, the processing of the measured and controlled radar data is complicated or generates large errors due to the existence of high-order derivatives and apparent angular acceleration. The accuracy of the measured data is greatly influenced.
Radar countermeasure reconnaissance is an indispensable important link in the field of information countermeasure, and plays an increasingly important role in mastering battlefield initiative. However, with the increasingly complex electromagnetic environment, new system radars are gradually dominant, single-sensor-based intelligence reconnaissance no longer has wide adaptability, and multi-sensor data fusion is used as a processing means for comprehensively analyzing intercepted information of different sensors, and has more accurate and more stable working performance than a single sensor. Therefore, the invention utilizes the data fusion algorithm based on the multiple sensors to improve the anti-interference capability of the reconnaissance system and obtain the radar parameter information with higher precision.
In the aspect of fusion algorithm, the traditional self-adaptive weighting fusion is based on the premise of minimum total mean square error, and the optimal weighting factors are distributed for each sensor, but abnormal data cannot be effectively eliminated. Bayesian inference calculates the posterior probability of the target based on Bayesian rule, has higher fusion precision, but needs prior knowledge as support. The Kalman filtering utilizes the statistical characteristics of a system model to determine a data fusion estimation value through recursive operation, but the method has strict requirements on the system model, and not only needs the system to provide an accurate state equation and an observation equation, but also needs the prior knowledge of the statistical characteristics of the system and observation noise.
In the face of a diverse electromagnetic environment, a fusion algorithm should be able to give ideal fusion results for a variety of complex data. Firstly, the method needs to have the capacity of eliminating abnormal data so as to improve the fusion precision and reduce the adverse effect of interference data. In addition, in general, the local expectation closer to the true value has a smaller corresponding local variance, and for a distributed fusion mode, different sensors are affected by uncertain factors such as environment, and the local expectation and the variance of each sensor do not necessarily strictly satisfy the above relationship, that is, even if the local expectation is close to the true value, the variance may be larger, and even if the local expectation is far from the true value, the corresponding variance may be smaller.
The data algorithm module is used for eliminating abnormal values by utilizing quartile dispersion, solving the weight of each sensor by comprehensively considering local expectation and variance, solving the weight of each sensor by adopting a consistency function to establish a support matrix for the local expectation, solving the weight of each sensor by utilizing self-adaptive weighting for the variance, combining the local expectation and the variance to obtain comprehensive weight, and finally weighting to obtain a fusion result;
as shown in fig. 5, the data algorithm module processes the signal data acquired by the antenna module according to the following steps:
step S1: identifying radar reflected wave data, and eliminating acquired abnormal data;
step S2: carrying out weight solving on the normal data;
step S3: and carrying out weighting processing on the result after the weight solution to obtain interference-free radar data.
In step S1, the outlier is removed by using a quartile method, and n data numbers of the radar reflection waves are sorted from small to large to obtain a group of detection sequences: d 1 ,D 2 ,…,D n Defining the quartile A on the test sequence c Is in the position N u (n +1)/4, lower quartile A b Is in the position N l 3(N +1)/4, N u Is e and the fractional part is f, then the expression of upper and lower quartiles:
Figure BDA0003549672090000111
and (3) obtaining the dispersion of the quartile:
d A ＝A c -A b 。
in step S1, for all local expectations, data whose expectation value is larger than the upper quartile by θ dA is defined as invalid data θ e [1,2]Is a threshold parameter, i.e. the interval for determining whether the data is valid is [ gamma ] 1 ,γ 2 ]：
Figure BDA0003549672090000121
Interval [ gamma ] 1 ,γ 2 ]The inner radar reflected wave data is considered to be valid data, interval [ gamma ] 1 ,γ 2 ]And the data of the external radar reflected waves are considered as abnormal data and are removed.
In step S2, after removing the abnormal values, calculating corresponding weights of the radar reflected wave data, determining the weights by using local expectation and variance, respectively, to obtain final integrated weights, for the local expectation, first solving a confidence distance between two expectations by using a consistency measure operator based on an exponential decay function, where an operator expression is:
d ij ＝exp(-(x i -x j ) 2 )
d nm ＝exp(-(D n -D m ) 2 )
further obtaining a confidence distance matrix D n From d nm D is more than or equal to 0 nm ≤1，d nm The smaller the degree of support of the nth radar reflected wave data by the mth radar reflected wave data is, the higher the degree of support of the mth radar reflected wave data is, the smaller the degree of support of the mth radar reflected wave data by the nth radar reflected wave data is, the higher the degree of support of the mth radar reflected wave data by the nth radar reflected wave data by the mth radar is nm The size of (c) gives a measure of the degree of support, let
s nm ＝1-d nm (n，m＝1，2，...，i)
s nm Representing local expectation D between two radar reflected wave data n And D m The mutual support degree between the data and the data is used to weight the data of the radar reflected wave, and the sum G of the nth column and the support matrix of the data of all the radar reflected waves is calculated by using the representation n The support degree of the nth radar reflected wave data is as follows:
Figure BDA0003549672090000122
obtaining radar reflected wave data weight H based on local expectation p Comprises the following steps:
Figure BDA0003549672090000123
determining variance weight and comprehensive weight, and obtaining the data weight H of each radar reflected wave by using a self-adaptive fusion algorithm for local variance A The method comprises the following steps:
Figure BDA0003549672090000131
in step S3, after obtaining the desired weight and the variance weight, the two weights are weighted averagely to obtain a comprehensive weight H:
Figure BDA0003549672090000132
and finally, weighting by using the comprehensive weight to obtain a fusion result of the radar reflected wave data.
The invention has the beneficial effects that: the system can complete corresponding functions according to the instruction information of the radar host, achieves indexes required by the system, accurately and intelligently tracks the target, works stably, and has strong anti-interference performance and reliability and high precision.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various equivalent changes, modifications, substitutions and alterations can be made herein without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims (10)

1. A high-precision radar level measurement and control system is characterized by comprising a signal receiving and reflecting module, an antenna module, a data algorithm module, an analog-to-digital conversion module, a high-frequency signal processing module, a touch screen display module and a power supply module;
the analog-to-digital conversion module is connected with the signal receiving and reflecting module, the high-frequency signal processing module and the touch screen display module, and is used for mutually converting an analog signal and a digital signal, and the high-frequency signal processing module is simultaneously connected with the antenna module;
the signal receiving and reflecting module receives signals collected by the antenna module, and the signals are processed by the data algorithm module and then transmitted out;
the touch screen display module is used for setting and adjusting data parameters of the system;
the high-frequency signal processing module is used for generating and processing a high-frequency signal;
and the power supply module is used for respectively supplying power to the analog-to-digital conversion module, the high-frequency signal processing module and the signal receiving and reflecting module.
2. The system as claimed in claim 1, wherein the antenna module sends control commands to the high frequency signal processing module via the serial communication bus RS-232 by using a local computer, and the high frequency signal processing module receives the control commands from the host computer and sends corresponding effective signals to the drivers of the corresponding motors to generate and process high frequency signals according to the requirements.
3. The high-precision radar level measuring and controlling system as claimed in claim 2, wherein the development of the circuit board part of the high-frequency signal processing module is mainly completed by a single chip microcomputer, and the model of the single chip microcomputer is AT89S 52.
4. A high accuracy radar level gauge control system as claimed in claim 3, wherein said single chip is used for signal processing of the control motor and the resolver-to-digital converter.
5. A high accuracy radar level gauging system as claimed in claim 4, wherein said data algorithm is programmed after the system has started to operate, and wherein when programmed, first, the system will complete all initializations to be configured, and second, the command flag is determined, and when the flag changes, the main function will invoke the subroutine.
6. The system as claimed in claim 5, wherein the data algorithm module processes the signal data collected by the antenna module by the following steps:
step S1: identifying radar reflected wave data, and removing collected abnormal data;
step S2: carrying out weight solving on the normal data;
step S3: and carrying out weighting processing on the result after the weight solution to obtain interference-free radar data.
7. The system as claimed in claim 6, wherein the data algorithm module, in step S1, eliminates outliers by using a quartile method, and sorts n data of radar reflection waves from small to large to obtain a set of detection sequences: d 1 ,D 2 ,…,D n Defining the quartile A on the test sequence c Is in the position N u (n +1)/4, lower quartile A b Is in the position N l 3(N +1)/4, N u Is e and the fractional part is f, then the expression of upper and lower quartiles:
Figure FDA0003549672080000021
and (3) obtaining the quartile dispersion:
dA＝A c -A b 。
8. the high accuracy radar level gauging system according to claim 7, wherein said data calculationA method module, wherein in the step S1, for all local expectations, defining data with expectation value larger than upper quartile by theta dA as invalid data theta epsilon [1,2]Is a threshold parameter, i.e. the interval for determining whether the data is valid is [ gamma ] 1 ,γ 2 ]：
Figure FDA0003549672080000031
Interval [ gamma ] 1 ,γ 2 ]The inner radar reflected wave data is considered to be valid data, interval [ gamma ] 1 ,γ 2 ]And the data of the external radar reflected waves are considered as abnormal data and are removed.
9. The system as claimed in claim 8, wherein in step S2, after removing the outliers, the corresponding weights of the radar reflected wave data are calculated, the weights are determined by using local expectation and variance, respectively, to obtain the final integrated weight, for the local expectation, the confidence distance between two expectations is first solved by using a consistency measure operator based on an exponential decay function, and the operator expression is:
d ij ＝exp(-(x i -x j ) 2 )
d nm ＝exp(-(D n -D m ) 2 )
further obtaining a confidence distance matrix D n From d nm D is more than or equal to 0 nm ≤1，d nm The smaller the degree of support of the nth radar reflected wave data by the mth radar reflected wave data is, the higher the degree of support of the mth radar reflected wave data is, the smaller the degree of support of the mth radar reflected wave data by the nth radar reflected wave data is, the higher the degree of support of the mth radar reflected wave data by the nth radar reflected wave data by the mth radar is nm The size of (A) gives a measure of the degree of support, let
s nm ＝1-d nm (n，m＝1，2，...，i)
s nm Representing local expectation D between two radar reflected wave data n And D m The mutual support degree between the data and the data is weighted by the support degree, and the sum G of the support matrix and the nth column of all the data of the radar reflected waves is calculated by the representation n Is then nThe support degree of the radar reflected wave data:
Figure FDA0003549672080000032
obtaining radar reflected wave data weight H based on local expectation p Comprises the following steps:
Figure FDA0003549672080000041
determining variance weight and comprehensive weight, and obtaining the data weight H of each radar reflected wave by using a self-adaptive fusion algorithm for local variance A The method comprises the following steps:
Figure FDA0003549672080000042
10. the system as claimed in claim 9, wherein in step S3, the desired weight and variance are obtained, and then weighted to obtain a composite weight H:
Figure FDA0003549672080000043
and finally, weighting by using the comprehensive weight to obtain a fusion result of the radar reflected wave data.
CN202210258381.8A 2022-03-16 2022-03-16 High-precision radar level measurement and control system Withdrawn CN114839600A (en)

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