87results about How to "Improve dynamic adaptability" patented technology

The invention discloses a measurement system of a relative altitude and a relative attitude of an air vehicle and a measurement method thereof. Four ultrasonic ranging modules are installed at different positions of the air vehicle, ultrasonic wave emitting and receiving of the ultrasonic ranging modules are controlled through an MPU, ultrasonic wave transmission time is calculated, pressure parameters, temperature parameters and humidity parameters of atmosphere are collected so that the transmission speed of the ultrasonic waves can be compensated, meanwhile by means of a range error compensation module, range errors of an ultrasonic ranging sensor are compensated, relative height data of the air vehicle and the ground are measured, a relative height calculation model and a relative attitude calculation model are built, and the precise relative height between the centers of wings of the air vehicle and a landing runway plane and attitude angle information of an ultrasonic installation plane relative to the runway plane are calculated. The measurement system and the measurement method improve precision and stability of measurement of the relative height and the relative attitude during landing of the air vehicle.

The invention discloses a vehicle-mounted positioning method based on multi-source information fusion, and the method comprises the following steps: 1, respectively obtaining the navigation information from each system; 2, carrying out the time-space registration of the navigation information from different systems; 3, carrying out the local filtering; 4, carrying out the information fusion; 5, outputting positioning information after information fusion, carrying out the reconfiguration of a main filter and a subfilter through an information distribution principle, and then returning to step 1. The invention innovatively provides the vehicle-mounted positioning method based on multi-source information fusion, and the method achieves the fusion of the position information provided by different positioning systems, improves the system redundancy, enables the positioning systems to complement each other's advantages, improves the dynamic adaptability of the systems, enables the total system to obtain the precision which is better than the precision of the local systems, improves the vehicle-mounted positioning capability, and enables a land-based weapon launching system to have the long-time and large-range maneuvering capability.

The invention discloses a method for improving the dynamic performance of an active pixel sensor (APS) star sensor. The method comprises the following steps: (1) establishing a dynamic performance analysis model of a star sensor based on parameters such as star energy, clear aperture, quantum efficiency, movement angular speed and signal to noise ratio according to a photoelectric conversion transfer path of starlight, and analyzing and determining dynamic performance parameters such as integral time, sensitivity and star detection probability in a field of view; (2) determining APS integral time according to factors such as the movement angular speed, the field of view, the resolution of an image detector and a star point diffusion function; (3) under the condition that a roller blind shutter of the image detector heavily affects the star diagonal distance of a star map at high movement angular speed, designing a star point position compensation and correction method for a special APS roller blind shutter integral manner; and (4) designing a double-frame star map processing mode of the star sensor, and estimating the angular speed of a spacecraft under the condition of high angular speed according to star point positions of a two-frame star map. By virtue of the method, the dynamic performance of the APS star sensor is improved.

The invention discloses an energy efficiency-oriented multi-agent deep reinforcement learning optimization method for an unmanned aerial vehicle group. The method comprises the steps of adopting an improved DQN deep reinforcement learning method based on Q learning, training and updating the neural network of each intelligent agent by using historical information of the unmanned aerial vehicle cluster to obtain channel selection and power selection decisions of each intelligent agent of the unmanned aerial vehicle cluster, training the neural network by using a short-time experience playback mechanism in the training process, and maximizing the energy efficiency value of the corresponding intelligent agent by using the optimization target of each neural network. According to the invention,a distributed multi-agent deep strong chemical method is adopted, and a short-time experience playback mechanism is set to train a neural network to mine a change rule contained in a dynamic networkenvironment. The problem that a convergence solution cannot be obtained in a large state space faced by traditional reinforcement learning is solved. Multi-agent distributed cooperative learning is achieved, the energy efficiency of unmanned aerial vehicle cluster communication is improved, the life cycle of an unmanned aerial vehicle cluster is prolonged, and the dynamic adaptive capacity of an unmanned aerial vehicle cluster communication network is enhanced.

The invention discloses a heterogeneous wireless network access selection method based on a fuzzy neural network, aiming to solve the problem of imbalance loading among networks in a network coverage environment. The access selection method comprises the steps of: 1. prejudging and preprocessing: a. reducing the number of users which need to be processed subsequently; b. computing received signalstrength difference (DRSS) of two networks and access system difference DP of the two networks; 2. obtaining a fuzzy judgment factor FSD by using an RBF fuzzy neural network, wherein the fuzzy judgment factor FSD is obtained by adopting the RBF fuzzy neural network by taking the received signal strength difference (DRSS) of the two networks and the access system difference DP of the two networksas input parameters; 3. access judgment: obtaining an access judgment result according to the fuzzy judgment factor FSD; if the fuzzy judgment factor FSD is less than 0.5, then accessing network 1; if the fuzzy judgment factor FSD is more than 0.5, then accessing network 2; and if the fuzzy judgment factor FSD is equal to 0.5, and then accessing a network with strong signal strength.

The invention discloses a variable-rigidity flexible drive joint. The variable-rigidity flexible drive joint comprises a joint shell, a joint motor and a harmonic reducer. The end portion of a motor shaft of the joint motor is connected with a wave generator of the harmonic reducer to serve as the input of the joint. The motor shaft is provided with a rigidity adjusting mechanism. A steel wheel of the harmonic reducer is fixed to one flange. The outer ring of the flange is matched with the joint shell through a bearing. A groove is formed in the flange and is in contact with one end of an elastic part. The other end of the elastic part is fixed. The deformable length of the elastic part is adjusted through the rigidity adjusting mechanism, and therefore flexible connection between the steel wheel and the joint is achieved, and a flexible wheel of the harmonic reducer serves as the output of the joint.

The present invention discloses a fine-grain multi-target passive positioning method on the basis of a RFID. The method provided by the invention is able to take the disturbance of multipath information as fingerprint information, and a multi-target positioning method in the prior art remove multipath or neglect multipath information, so that the method provided by the invention is able to realize the calculation of fine grain position, and other methods can only indicate the substantial position of an object. The method provided by the invention is able to accurately perform fine grain multi-target positioning and fill up defects of the multi-target positioning algorithm in the aspect of positioning precision, and has good dynamic adaptability of the environment and low economic cost.

The invention provides a passive type moving target locating method on the basis of Doppler frequency shift. The method comprises the specific steps that firstly, a scene is set; secondly, a locating signal is generated; thirdly, the locating signal is located, a locating angle is determined; fourthly, angle information, corresponding to a directive antenna, of three beacons is determined according to sub-channel designators stored by the three beacons, and therefore the position of a moving target is determined. According to the method, the directions, relative to the three beacons, of the target can be determined according to Doppler influence on beacon sending frequency from movement of the moving target, the single moving target can be located in the passive locating scene, little locating equipment, short locating time and low locating cost are used, and the effect of locating the passive type moving target is improved.

The invention relates to a single-axis accelerometer and three-axis magnetic field sensor based attitude measurement system and an attitude measurement method thereof. The system includes: an accelerometer, a three-axis magnetic field sensor, a GNSS module and a data processing module. The accelerometer is a Z axial direction single-axis accelerometer in orthogonal arrangement with a forward shaft and used for measuring gravitational acceleration component so as to obtain the triangle relationship between a ground carrier's roll angle and pitch angle. The data processing module is used for acquiring geomagnetic field model, geomagnetic inclination information and magnetic declination information according to a position information look-up table, and combining the triangle relationship between the ground carrier's roll angle and pitch angle and the three component arrays of a geomagnetic field under a carrier coordinate system to finally work out a course angle, the pitch angle and the roll angle. The new attitude measurement method provided by the invention can realize exact calculation of the carrier attitude angle under a carrier stationary or low speed moving state, can reduce a measurement amount, and avoids introduction of more measurement noise.

The invention relates to the field of satellite communication, in particular to a satellite network dynamic routing method based on inter-satellite link attributes. The method comprises the following steps: collecting a static snapshot sequence diagram of a satellite network, and constructing a satellite network spatio-temporal evolution diagram; enabling a controller node to collect state information of a satellite node in real time, and respectively calculating a link SNR, link survival time and a dynamic utility value of a satellite cache; giving a weight to the dynamic utility value of each inter-satellite link attribute by adopting a self-adaptive maximum deviation algorithm based on multi-attribute decision making, and constructing a weighted satellite network spatio-temporal evolution diagram; obtaining an end-to-end reachable path of the satellite based on the weighted satellite network spatio-temporal evolution diagram, and establishing an optimization model of link utility; and enabling the controller node to select a transmission path by using the optimization model, and determining a reliable satellite end-to-end transmission path. According to the method, the system routing path can be optimized according to the link state information, so that the network throughput is improved, the packet loss rate is reduced, and the dynamic adaptability is relatively high.

The invention discloses a method for inertial information assisting a GNSS tracking loop. The method includes the steps that according to the carrier position, speed and accelerated speed information provided by an inertial navigation system, combined with the information such as local time and a satellite ephemeris, Doppler shifts and Doppler shift change rates of all channel satellites of a GNSS receiver are calculated in real time, the difference information of a tracking loop carrier frequency shift measurement value and a corresponding Doppler shift calculation value is taken as an observation quantity, frequency deviation caused by mechanical vibration of a carrier and crystal oscillator frequency drift of the receiver is calculated by the adoption of an alpha-beta filtering method, a carrier frequency shift predicted value is obtained to correct the tracking loop in a feedforward mode, and the step of inertial information assisting the GNSS tracking loop is finished. The dynamic stress action on the tracking loop by high dynamic is reduced, frequency deviation caused by mechanical vibration of the carrier and crystal oscillator frequency drift of the receiver is eliminated, dynamic adaptability and navigation stability of the GNSS receiver are improved, and the application prospects are wide.

The invention relates to a self-adaptive dual-harmony optimization method which comprises the following steps of: initially optimizing a harmony memory base and putting a generated initial solution into the harmony memory base; then equally dividing the initial solution into two groups, i.e. a master harmony library and an auxiliary harmony library respectively and respectively determining the tone trimming probabilities and the tone trimming bandwidths of the master harmony library and the auxiliary harmony library; iteratively searching from the opposite direction under the situation that the algorithm convergence rules are not satisfied to obtain two groups of new solutions; and replacing a solution in the existing memory bank by using an optimal solution in the two groups of new solutions obtained by multiple iteration, thereby obtaining an optimal solution to finally achieve the wonderful harmony. The self-adaptive dual-harmony optimization method has the beneficial effects that tone trimming probability and tone trimming bandwidth factors are continuously adjusted to improve the dynamic adaptability of an algorithm and the coordination ability of local search and full search; two groups of master and auxiliary harmonies which are different in the search direction and are mutually coordinated are constructed, so that the search range is expanded, the iteration number is reduced, and the global optimization is more quickly realized; the problem of complicated function optimization is solved; and the full search ability and the convergence rate are good.

The invention discloses an RFID-based multi-target passive-type indoor activity identification method, which takes perturbation of RFID tag phases caused by human activities as fingerprint information and obtains activity situations of multiple targets by using perturbation of different tag phases caused by activities of many persons. However, current indoor activity identification methods are mainly for a single target, and cannot be applied or lead to big activity identification errors in multi-target indoor scenes. The method of the invention realizes multi-target activity identification without the requirement that targets carry devices, solves the defects of indoor activity identification in terms of target quantity, achieves good dynamic adaptability to the environment, and is low in economic cost.

The invention discloses an audio and video remote monitoring method based on 3G (the 3rd generation telecommunication) network and an audio and video remote monitoring system based on 3G network. The method comprises the following steps: 1) embedded terminals and a monitoring server are provided; 2) the embedded terminals collect onsite audio and video in real time; 3) the embedded terminals detect network delay in real time and dynamically regulate QP ( quasi peak ) value, frame rate and code rate, perform H264 encoding the onsite audio and video according to the QP value, the frame rate and the code rate, and then send the encoded audio and video to the monitoring server; and 4) a currently embedded terminal receives the encoded audio and video according to a control command from the monitoring server, decodes the audio and video and then outputs the decoded audio and video to users. The system comprises the monitoring server and a plurality of embedded terminals, wherein each embedded terminal comprises an audio and video collecting module, a central processing unit, a network receiving and sending module, emergent monitoring keys and an audio and video output module; and the central processing unit includes a delay detecting module, an encoding parameter regulating module and an audio and video encoding module. The audio and video remote monitoring method based on 3G network and the audio and video remote monitoring system based on 3G network according to the invention have the advantages of good bandwidth dynamic adaptability, fluent audio and video, and good monitoring quality.

The invention relates to a credibility measuring method combining a Bayesian algorithm and a MapReduce. The credibility measuring method combining the Bayesian algorithm and the MapReduce comprises the following steps that S01, a Bayesian filter algorithm is used for carrying out credibility evaluation on behavior records generated in the process of mobile terminal interaction, statistics is carried out on the prior probability of training data centralization, the posterior probability of the behavior records is calculated through a Bayes formula, and the maximum posterior probability is selected to serve as the credibility of the behavior records; S02, probability distribution evaluation is carried out on credible records through a Bayesian inference algorithm with a Dirichlet process, and prediction of the credibility of mobile terminals can be obtained; S03, selection of a characteristic value is achieved through an information gain algorithm. The credibility measuring method combining the Bayesian algorithm and the MapReduce achieves high efficiency, safety and neutrality in the process of calculation and storage of the credibility with the help of a cloud computing platform, and safe storage and high-performance calculation of data are ensured.

The invention discloses an intelligent power grid abnormal power consumption behavior detection method. The method comprises the following steps: power consumption behaviors of users are described through change of different power consumption service types of electric energy consumption amounts of the users along with time so that power consumption features of the users are fully reflected; the users are clustered by use of similarities between the power consumption behaviors of the users, deviations of abnormal power consumption behaviors from normal behavior modes are depicted by use of mutual association between the power consumption behaviors of the users in the same user cluster and correlation between the power consumption behaviors of the users and historical power consumption behaviors, such that effectiveness of abnormal power consumption behavior detection is guaranteed; through analyzing accumulated user power consumption behavior data in a fixed time interval, under the condition that the detection precision requirement is satisfied, too much noise is prevented from being introduced in analysis of vast real-time data, and the method is enabled to have quite good dynamical adaptability; and through analyzing the accumulated user power consumption behavior data in the fixed time interval, the original data amount is reduced, and the detection method disclosed by the invention can satisfy the requirement for real-time performance.

The invention belongs to the trust management field of large-scale distributed network application and particularly relates to a self-adapting dynamic trust weight evaluating method which is particularly fit for various large-scale open distributed applications of gridding, pervasive computing, P2P (peer-to-peer) computing, Ad hoc (mobile ad hoc networking), electronic commerce and the like based on Internet as a basic platform. On the basis of existing direct trust evaluating method based on historical function and a feedback trust polymerization technology based on path function, the invention provides a method for using two parameters including confidence factor and feedback factor to automatically establish and dynamically adjust weight calculated by fusing direct trust and feedback trust, the invention overcomes the defect of confirming the weight subjectively in common use before, thus leading the invention to have good scientificity and higher practical application value.

The invention belongs to the technical field of smart home, and discloses a smart home system based on the Internet of Things. The smart home system is provided with a control device, a smart home application running virtual machine and a heterogeneous device; the control device is connected with the smart home application running virtual machine through Wifi; the smart home application running virtual machine is connected with the heterogeneous device through a conducting wire, and each part in the control device is connected to the smart home application running virtual machine through the Wifi, and the smart home application running virtual machine realizes the function control of the heterogeneous device through the conducting wire connection. smart home system has an open, flexible and scalable compatible architecture, and provides the existing platform with the ability to rapidly expand value-added services.

The invention relates to an active magnetic suspension accelerometer with high alignment, high stability and high resolution; the active magnetic suspension accelerometer comprises a short circuit turn angle sensor, a permanent magnetism torquer, a liquid float plus jewel bearing and active magnetic suspension centering, and double-end bellows volume compensation; when an inertia acceleration applies on a floater, a vertical pendulum deflects, the angle sensor senses the deflection angle, a force feedback loop forms a control current, the control current is applied to a permanent magnetism torquer control coil, thus restoring the vertical pendulum back to the zero bit; control current size symbols are matched with inertia acceleration sizes and directions. Said measures can improve the accelerometer precision; the precision of the accelerometer working under the gate state can improve by almost an order of magnitude when compared with a liquid floating integration pendulum accelerometer. The accelerometer with the active magnetic suspension technology is firstly applied in our nation, thus greatly improving the accelerometer stability and dynamic adaptability; the accelerometer canbe applied to an inertia space navigation system.

An account resource reservation and distribution method in IMS multi-service On-line Billing; the operation step comprises: enlarging message format of CCR in DCCA protocol alternated between charged entity device of IMS and OCS, increasing attribute value BI of business bandwidth information, reporting CCR message updating the request type to the OCS by the charged entity device; OCS initializing, stopping or updating according to the different types of the received CCR message; dynamically correcting the business standard resource according to QoS level running in business example, executing the business standard resource updating arithmetic; executing resource reservation arithmetic and resource recovery arithmetic based on the standard resource; or executing resource redistribution arithmetic, redistributing the recovered resource to the new business example and the business example of the recovered resource; OCS returning CCA message to the charged entity device. The method can ensure high account resource utilization rate and not cause large network and system resource expenditure.

The invention discloses a dynamic self-adaptation positioning method of an underwater wireless sensor network, and belongs to the technical field of positioning of the underwater wireless sensor network. The dynamic self-adaptation positioning method of the underwater wireless sensor network comprises the following steps that firstly, an anchor node evaluates the accuracy of the coordinates of the self-statement position; secondly, a node to be positioned builds a dynamic updatable positioning set; thirdly, the positioning set carries out multi-hop distance estimation with the deviation corrected in a self-adaptation mode; fourthly, the position accommodation space of the node to be positioned is solved; fifthly, coordinate estimation and accuracy evaluation of the node to be positioned are carried out. The accuracy of the coordinates of the statement position of the anchor node is evaluated and calibrated on line, the adverse influence on positioning performance from the position error of the anchor node is reduced, the accuracy of multi-hop distance estimation is improved through multi-hop distance estimation with the deviation corrected in the self-adaptation mode, the on-line cognition and dynamic self-adaptation capacity of a complex positioning environment of a sensor network node are improved, ad the positioning performance of the underwater wireless sensor network is improved.

The invention relates to a peer-to-peer network trust degree measurement model based on Bayes under cloud architecture. The peer-to-peer network trust degree measurement model based on the Bayes under the cloud architecture is characterized in that confidence coefficient value calculation is conducted on trust data of nodes; if the confidence coefficient value is less than a threshold value, own trust data are insufficient for conducting trust calculation and trust calculation is transferred to be conducted on a cloud platform which has more trust data and recommended information; otherwise, the trust calculation is conducted locally. The peer-to-peer network trust degree measurement model based on the Bayes under the cloud architecture solves the problems of single point failure and high time delay of a traditional centralization type trust model and overcomes the boundedness of a distributed type trust model in the fields of data storage and security.

An online system more efficiently streams multimedia content over the Internet for play back on client devices with varying computing power and network bandwidths by generating enhanced manifest files that more efficiently identify suitable media representations of the multimedia content. Each media representation has multiple media segments according to predefined byte ranges and a manifest file, which identifies location of the media file, bitrates, resolution, byte range, total duration, and other metadata. The online system customizes a manifest file for a user based on various factors including device capacity, network connectivity type and geolocation of the user. The online system also generates manifest fetch commands, which more efficiently fetch media segments for streaming. In response to changes of streaming server and media file (e.g., increased popularity), the online system dynamically updates corresponding manifest files.

The invention relates to a wind-power-generation-containing two-region interconnected power grid automatic generation control optimization method. The method comprises the steps of: establishing an automatic generation control space state model, wherein the model is a two-region interconnected system including hydroelectric power, a small fossil power plant and wind power; according to the established space state model, constructing a new cost function; forming a control variable by an output variable and an output feedback gain matrix so as to determine an input variable; in a closed-loop system, constructing a Lyapunov function to obtain a Lyapunov equation; and based on the Lyapunov equation, deriving a Hamilton function, and obtaining optimal values of corresponding parameters so as toobtain an automatic generation control optimization result of the established model. A control strategy disclosed by the invention has good dynamic adaptability and can reinforce coordination among aplurality of control regions. The invention solves the problem of frequency fluctuation of a power system, which is caused by ever-increasing installed capacity of wind power and inherent randomnessand fluctuation of the installed capacity of wind power.

The invention discloses an integer ambiguity Kalman filtering algorithm based on inertial navigation assistance. The integer ambiguity Kalman filtering algorithm comprises the following steps: acquisition tracking and synchronization for a satellite; observation measurement and extraction; determination of position and speed calculation of the satellite; establishment of a Kalman filtering model;filtering estimation; and calculation of an integer ambiguity. The integer ambiguity Kalman filtering algorithm has advantages as follows: the integer ambiguity Kalman filtering algorithm utilizes a Kalman filter based on the inertial navigation assistance to estimate a float solution of the integer ambiguity, improving dynamic adaptability of the ambiguity solution. The algorithm is simple in useand free from complicated or huge-computation equations. The real-time performance and computation burden of the algorithm can be ensured to implement on DSP or FPGA hardware platforms by arithmeticprogramming, and easy to implement in engineering.

The invention provides a single beacon locating method based on rotary RSS (received signal strength). According to the single beacon locating method based on the rotary RSS, the distance and the direction constraint of sending nodes relative to receiving nodes are obtained according to rotary RSS information, collected when a person rotates around a wireless receiving device, of a plurality of sending devices, so that the positions of all sending nodes relative to the receiving nodes are obtained; as long as the absolute positions of the receiving nodes all are known, the absolute positions of all the sending nodes can be obtained. The single beacon locating method based on the rotary RSS, which is disclosed by the invention, does not need to depend on special devices, and is an un-discussed new locating method in the field of wireless location; the location of a plurality of unknown nodes is finished in a single beacon scene, the limitation of a basic trilateral location algorithm to the minimum beacon number is broken through, the dynamic adaptability to the environment is good, and the communication overhead is lower.

The invention discloses a lithium battery remaining capacity estimation method based on integral Kalman filtering. The method comprises the steps: 1, establishing an equivalent circuit model of a lithium battery; 2, establishing a state equation and an observation equation according to the equivalent circuit model; 3, performing parameter identification on parameters in the equivalent circuit model; 4, establishing a state equation of discrete time by taking SOC as a state variable; 5, determining the size of a Gauss-Hermite integral solving point and a weight corresponding to the integral solving point; 6, continuously estimating the residual electric quantity of the lithium battery in the discharging process by adopting an operation process of integral Kalman filtering. The method is simple in step and convenient to implement, estimates the residual electric quantity of the lithium battery through the integral Kalman filtering algorithm, is good in dynamic adaptability to the lithiumbattery and high in estimation precision, can be effectively applied to the fields of new energy vehicles and the like which have high requirements on the estimation instantaneity and the estimationprecision of the residual electric quantity of the lithium battery, and is remarkable in effect and convenient to popularize.

The invention discloses a flow anomaly detection method based on a multi-order Markov chain, and the method comprises the steps: building a flow normal behavior contour based on a Markov model throughnormal historical flow data, and obtaining the parameters of the Markov model through training; based on the EWMA and a sliding window mechanism, constructing a judgment threshold value at the momentt by utilizing the predicted value at the moment t and the standard deviation of the occurrence probability of the network flow in the sliding window; judging the state of a data packet of the network flow at the moment t so as to convert the network flow at the moment t into a state sequence It; calculating the occurrence probability Pr(It) of the state sequence It by using a trained Markov model, and comparing the occurrence probability Pr(It) with a judgment threshold sigma t at the moment t; if Pr(It) is larger than sigma t, judging that the network flow at the moment t is normal flow; otherwise, judging that the network flow at the moment t is abnormal flow.

The invention relates to the technical field of error compensation, and discloses an error compensation method of a wireless positioning system. The method comprises the following steps of: through fully considering the characteristic that the method in the prior art is easily affected by positioning scenes, environment factors and the like, on-line acquiring system positioning error information as data of a training data set through reference points; training the training data set by a support vector regression method so as to obtain a regression estimate model of the system positioning error; when the scenes or environment changes, updating the training data set to obtain a new regression estimate model of the system positioning error; and finally performing self-adaptive error compensation based on the model, so as to improve the environment self-adaptive performance and system positioning precision of the system.

The utility model discloses a receiving machine deep combination implementation method based on the Big Dipper second-generation satellite navigation system. Assisted by an inertial navigation system, accurate speed assistance is provided for a receiving machine carrier wave tracking loop, a carrier wave tracking loop closed loop is utilized to provide assistance for a code tracking loop to eliminate most dynamic factors of carriers in the carrier wave tracking loop and the code tracking loop so as to reduce the orders of the carrier wave tracking loop and the code tracking loop, so that the noise bandwidth is decreased, the situation that the tight combination technology cannot improve the robustness and the measured value quality of a satellite signal tracked by a receiving machine is overcome; after the receiving machine loop is assisted, the filter bandwidth can be narrowed, and the technical effects that the high-dynamic adaptive capacity, the tracking sensitivity and the anti-interference ability of the receiving machine are improved are realized.