106 results about "Interference theory" patented technology

The invention discloses a distributed optical fiber oil channel leakage monitoring method and device based on interference theory. The monitoring system needs to lay an optical cable along the channel, and forms a fiber micro oscillation sensor with the fiber in the cable. When the channel has leakage, it will generate leakage noise, thus the fiber micro oscillator sensor can measures the micro oscillation and stress change around the channel, and it can fix on the leakage position quickly and accurately. The device is made up of distributed fiber micro oscillation sensor, guiding fiber and micro oscillation detector. The technology not only can detect the leakage, but also can detect the event which can cause the leakage, and it can send out alarm and accurate localization. The device has high sensitivity and localization precise, and the disturbance ability is strong, and it is reliable.

The invention discloses a method and a system for resisting dense forwarding type defraud interference of an airborne radar, and the resistance of dense forwarding type defraud interference is realized through an interference scout module and an interference filter and elimination module. Interference scout is used for carrying out the PD (probability of defraud) treatment on data received by a radar; the CFAR (constant false alarm rate) detection is carried out on data in a clear area; a detection result direction of arrival is estimated; an interference direction of arrival is estimated with combination of the detection result of a plurality of wave positions. In the interference filter and elimination treatment, a sum beam pointing to the interference direction is formed according to an interference scout result; the sum beam pointing to the interference direction is used as an auxiliary passageway, an existing space passageway is used as a main passageway, the method of GSC (gain scheduling control) is adopted to filter and eliminate interference, and the channel covariance matrix of the interference is estimated according to an interference sample selected from the clear area. By adopting the method and the system, the difficult problem of inhibition on dense forwarding type defraud interference is solved, the dense forwarding type interference is fundamentally filtered and eliminated, false alarms caused by the dense forwarding type interference are reduced, adverse effects on a CRAR detection threshold and the STAP (space time adaptive processing) performance are eliminated, the detection performance of a radar target is improved, the system is simple and easy to realize, and an engineering application value is provided.

The invention discloses a time-dependent fatigue reliability analysis method based on bilinear cumulative damage. The method includes the steps that 1, the probability distribution type and statistical characteristic parameter of fatigue life data are determined; 2, the appropriate reference life is selected, and a bilinear cumulative damage physical model is built; 3, according to the bilinear cumulative damage physical model, a probability cumulative damage model is built; 4, according to the stress-strength interference theory, a time-dependent fatigue reliability model is built; 5, a reliability curve is drawn and compared with an experimental result; the characteristics of a crack initiation stage and a crack propagation stage in the fatigue failure process and the randomness in the damage accumulation process are comprehensively considered, the bilinear damage theory serves as a modeling base, the probability cumulative damage model is built, through the combination with the stress-strength interference theory, the time-dependent fatigue reliability model based on cumulative damage and critical damage is built, the time-varying characteristics of fatigue loading and the dynamic behavior of the damage accumulation process are reflected, and the reliability prediction in the whole fatigue life cycle is achieved.

The invention belongs to the technical field of communication, and relates to an interference type identification method. The interference type identification method provided by the invention can comprise the following steps: carrying out interference detection and interference identification on hostile interference in a wireless communication system in a complex electromagnetic environment; and then jointly deciding the condition of the current electromagnetic environment, and classifying the interference types in an interference environment, the existence of interference is mainly determined from two aspects of time domain and frequency domain in the interference detection; in the interference identification, feature parameters are mainly extracted from the time domain, the frequency domain and the time-frequency domain, the interference is divided into time domain interference, frequency domain interference and sweep frequency interference by using a decision tree, and a part of interference is identified in detail; and the feature parameters extracted by the interference type identification method provided by the invention have relatively good robustness and are not sensitive to the interference and noise ratio, and relatively good interference identification performance can be obtained when a decision tree judgment method having relatively low algorithm complexity is used.

The invention belongs to the technical field of wireless communication, and relates to an anti-interference method for communication based on deep deterministic gradient reinforced learning. The method provided by the invention comprises the steps of firstly building an interference environment model according to the quantity of interference sources and a wireless channel model; building a utilityfunction according to a legal user communication quality index, using the utility function as a return in learning; forming spectrum information sampled at different time slots into a spectrum time slot matrix, and describing an interference environment state by using the matrix; and then building a convolutional neural network according to a deep deterministic gradient reinforced learning mechanism, and when an anti-interference decision is made, an environment state matrix achieves anti-interference strategy selection of the corresponding state in a continuous space via a target actor convolutional neural network. According to the method provided by the invention, the continuous anti-interference strategy selection in communication is completed based on the deep deterministic gradient strategy reinforced learning mechanism. The quantization error caused by quantized discrete processing on the policy space is overcome, the quantity of cells output by the neural network and the network complexity are reduced, and the anti-interference algorithm performance is improved.

The invention proposes a signal-level fusion networking radar anti-cheating interference method under object signal correlation, and the method can achieve the effective discrimination of false targets generated by different cheating interferences. The method comprises the steps: 1, enabling each junction radar to receive echo data and calculate a corresponding noise power; 2, building slow-time random complex envelope sequences of each point target at a plurality of junction radars; 3, estimating the mean power of each point target at each junction radar; 4, enabling the slow-time random complex envelope sequences of the same point target at the plurality of junction radars to be combined in a paired manner to form a plurality of envelope groups, and estimating a correlation tolerance; 5, calculating a detection threshold range; 6, searching an optimal detection threshold; 7, judging whether the correlation tolerance is greater than the optimal detection threshold or not: judging that the envelope groups pass through false target examination if the correlation tolerance is not greater than the optimal detection threshold, or else, marking two corresponding point targets as false targets; 8, eliminating the false targets.

The invention relates to an aircraft full-section control method based on the anti-interference technology. For an aircraft full-section control problem under unknown nonlinear dynamics, aerodynamic parameter uncertainty and external disturbance, the method comprises a step of establishing an aircraft six-degree-freedom model containing the above multi-source interference, converting an attitude dynamics model into an integral series type by linear state transformation and calling the uncertainty, the external disturbance and the unknown nonlinear dynamics as total disturbance, and representing with an expansion state, a step of designing an extended state observer to quickly estimate the aircraft total disturbance to obtain an interference estimation value, a step of designing an aircraftattitude controller based on active disturbance rejection control, and a step of designing attitude command correction based on a centroid motion state to complete the aircraft full-section control method based on the active disturbance rejection control. The invention realizes the full-section control of a level flight section and a going down section of an unpowered reentry vehicle, and the method has the characteristics of high robustness and easy engineering realization and is suitable for various types of flight systems requiring unpowered reentry.

The invention claims a method and system for detecting overshooting of a wireless network. The method comprises the following steps: determining the interference region of an estimated base station cell, wherein the interference region comprises a region which is located in the maximum coverage area of the estimated base station cell and located outside the ideal coverage area of the estimated base station cell; obtaining the data of sampling points in the interference region of the estimated base station cell and each target base station cell in the interference region; calculating interference factors of the estimated base station cell to each target base station cell; counting each interference factor; calculating the total overshooting decision factor of the estimated base station cell; determining the estimated base station cell to be overshooting when the total overshooting decision factor is more than a first threshold. By utilizing the method and system provided by the invention, the interference factors of the signals among cells are fully considered, and the accidental factor of the overshooting in the test data is filtered, thus the determination of overshooting is ensured to be more accurate.

The invention discloses a non-linear time-varying process fault monitoring method based on high efficiency recursion kernel principal component analysis and belongs to the fault detection and diagnosis technology field. The method comprises steps that data having non-linear and slow time-varying characteristics and containing faults is acquired from a Tennessee Eastman process simulator, a Gauss kernel function is utilized to project the acquired normal data to the high-dimensional characteristic space and is centralized, an initial offline monitoring model is established, and a kernel densityestimation function is employed to determine control limit; secondly, when new process data is acquired, through introducing a first-order interference theory method, a model is directly updated based on a characteristic value and a characteristic vector acquired in the offline model, the new data is projected to the updated kernel space and the residual error space to calculate T2 and SPE statistics; when the corresponding control limit is surpassed, occurrence of a monitoring fault is determined, otherwise, the whole process operates normally. The method is advantaged in that two problems are mainly solved, 1), a problem of relatively high false alarm rate generated during fault monitoring in the non-linear time-varying process of kernel principal component analysis is solved; and 2), aproblem of relatively high load existing in a recursion algorithm based on characteristic constant decomposition is solved.

The invention discloses a full-field optical coherence tomographic three-dimensional medical imaging device and a full-field optical coherence tomographic three-dimensional medical imaging method. The device comprises a Kohler illumination part, a reference arm, a sample arm, an imaging lens and an area array CCD detector; according to the method, piezoelectric ceramics are adopted for phase shift of a reference mirror according to the white light low-coherence interference theory; the optical path of the two arms is changed; CCD is used for receiving an interference signal; the interference signal is processed by a computer to obtain a two-dimensional fault map of a sample; finally an electric control displacement platform is used for axial scanning to obtain three-dimensional information, wherein a single chip can be used for emitting two different signal modulation piezoelectric ceramics; the CCD and the electric control displacement platform for the two arms correspond to two demodulation modes. According to the device and the method disclosed by the invention, the sample needs not to be subjected to the treatments such as slicing, dyeing and fluorescence labeling; frozen sections and paraffin sections which have the defects such as complex preparation and low resolution ratio can be replaced; a handhold medical instrument can be made for submicron-grade in-vitro imaging or in-vivo imaging of biological tissues.

The invention discloses an all optical-fiber current sensor based on magnetic fluid and a multi-mode interference structure. The all optical-fiber current sensor comprises a signal detection unit and a sensing unit. The signal detection unit comprises an SLD light source, a 50:50 optical fiber beam splitter, an adjustable optical fiber attenuator, a photoelectric balance detector, a data collection card, a computer, a power-on coil and a programmable power source. The sensing unit comprises a multi-mode coreless optical fiber arranged in a quartz capillary tube, the portion between the quartz capillary tube and the multi-mode coreless optical fiber is filled with magnetic fluid, the two ends of the multi-mode coreless optical fiber are respectively connected with single-mode input and output optical fibers in a welding mode, and the two ends of the quartz capillary tube are sealed by optical solidification glue. According to the all optical-fiber current sensor based on magnetic fluid and the multi-mode interference structure, the sensitivity of the magnetic field generated by the magnetic fluid to the currents and the multi-mode interference theory are used, the change relation between light intensity and currents is directly detected and output to achieve the purpose of detecting currents, and the defect that the polarized light detection method adopted by a traditional all optical-fiber current sensor is not stable is overcome.

A system is disclosed for detecting and calculating the level of ambient and / or environmental noise, such as electromagnetic interference generated by electric power lines, ambient lights, light dimmers, television or computer displays, power supplies or transformers, and medical equipment. In some embodiments, the system performs frequency analysis on the interference signal detected by light photodetectors and determines the power of the interference signal concentrated in the analyzed frequency bands. The worst-case interference level can be determined by selecting the maximum from the computed power values. In some embodiments, the determined interference signal power can be compared with the noise tolerance of a patient monitoring system configured to reliably and non-invasively detect physiological parameters of a user. The results of the comparison can be presented to the user audio-visually. In some embodiments, the system can be used to perform spot check measurements of electromagnetic interference.

The invention relates to the field of mobile communication, in particular to a construction method and system of an interference type recognition model. The construction method of the interference type recognition model comprises the following steps: generating a neural network model for interference type recognition based on DNN technology; obtaining interference waveform data from interference signals, marking the interference waveform data according to the interference type of the interference signals, obtaining interference data samples according to the interference waveform data and the corresponding marked interference types, and forming an interference data sample set; selecting a number of interference data samples randomly from the interference data set to form an interference data training set, and training the neural network model according to the interference data training set; saving the model parameters of the neural network model to obtain the interference type recognition model if the training result reaches preset conditions. The interference type recognition model can quickly recognize the type of the interference, therefore, the waste of resources is reduced, andthe classification efficiency of interference types is improved.

The invention discloses an atmospheric phase screen extraction method based on ground-based SAR (synthetic aperture radar) interference. Atmospheric phase is extracted according to a ground-based radar differential interferometric phase model on basis of a least squares fitting linear deformation and time-space filtering method. The ground-based radar differential interferometric phase model has a full consideration of the ground-based radar imaging mechanism and the differential interference theory so as to extract an atmospheric phase screen. A PS (permanent scatterer) point selection method of three levels, amplitude dispersion index, correlation index and phase stability, is provided, the atmospheric phase screen of radar data of each scene is finally obtained by means of Kriging interpolation, and accurate extraction of the phase generated under atmospheric interference has an important role on improving radar interferometric precision. Correctness of the method is verified by measured dam data, and the method is of certain actual application value and universality.

The invention discloses a metal structure fatigue reliability analyzing and optimizing design method based on damage mechanics. The method includes the steps of establishing a parameterized geometric and finite element model according to the key metal structure prone to fatigue through the uncertainty between the interval vector metric structure and material and the damage parameters, and a fatigue life interval range is calculated through the combination of an interval finite element and damage mechanics finite element analysis method; the fatigue reliability analysis of the structure is further achieved through a non-probability interval interference theory; finally, the complete optimization iteration process is achieved with the structure size as the design variable, the reliability degree as the constraint condition and the structure weight as the target function through a global optimization algorithm, and the optimal design variable result found through an output algorithm serves as the final structure optimizing design scheme. By means of the method, the sensitivity of the scheme itself to the design parameters is overcome, the aims of being smallest in weight and making fatigue reliability meet requirements can be achieved under the condition that the structure meets bearing conditions, and thus the design scheme is more economical and reasonable.

The invention relates to a frequency domain de-interference method and a device thereof based on a two-stage adaptive threshold decision, wherein the method comprises the following steps of: receivinga useful signal and an interference signal, processing both signals into a zero intermediate frequency signal, and windowing in two ways; performing FFT transformation to the two-way windowed data streams, and acquiring the frequency band portion of the useful signal; performing an iterative operation on the power of the useful signal, dividing the iteratively filtered power signal into a plurality of power blocks, calculating a peak-to-average ratio of the power blocks, and setting a decision threshold adjustment factor according to the peak-to-average ratio of the power blocks; calculatingan interference detection threshold to calculate all position indexes exceeding the threshold, and performing de-interference to obtain the data after interference suppression; sequentially performingthe IFFT transformation, inverse windowing processing and truncating of both ends of the data on the data after interference suppression, so as to acquire time domain intermediate signals; overlapping and outputting the two-way time domain intermediate signals. The method and system provided by the invention are capable of more accurately addressing the effects of narrowband and mid-band interference on signal quality.

The invention discloses a multi-objective main lobe anti-interference method based on feature matrix joint diagonalization, belongs to the technical field of radar anti-interference, and particularlyrelates to a multi-target blind source separation anti-main lobe interference method. The method comprises the steps of firstly, performing modeling under the condition that multiple objectives are disturbed by a main lobe; then, separating out an interference component and a target echo component by utilizing JADE; and finally, according to a matched filtering principle, enabling the target echocomponent obtained through blind source separation to pass through a matched filter, and finally inhibiting the interference to realize objective detection. The simulation shows the effectiveness of the method, and an algorithm does not need prior information of interference signals; various types of interferences can be inhibited; and therefore, the method has general applicability.

The embodiment of the present application provides a cognition-based deceptive anti-interference method and device in an unmanned aerial vehicle network and belongs to the technical field of wirelesscommunications. The method comprises the following steps: determining whether data transmission exists in the progress of a first unmanned aerial vehicle in the unmanned aerial vehicle network, and whether the data transmission is interfered by a first interference signal; if both the determination results are yes, obtaining a network parameter of the unmanned aerial vehicle network; determining an optimal spoofing channel according to the network parameter and a pre-stored spoofing channel selection algorithm; determining an optimal spoofing revenue power according to the network parameter and a pre-stored spoofing power allocation policy; if the optimal spoofing revenue power is greater than a preset revenue threshold, sending the pre-stored spoofing signal through the optimal spoofing channel based on the optimal spoofing revenue power, to a second unmanned aerial vehicle in the unmanned aerial vehicle network for receiving the acquired data corresponding to the data transmission. By adoption of the cognition-based deceptive anti-interference method and device in the unmanned aerial vehicle network in the invention, the anti-interference effect of the unmanned aerial vehicle canbe improved.

The invention provides a networking radar anti-cheating interference method based on signal level fusion, and the method can achieve the effective discrimination of false targets generated by different cheating interferences. The method comprises the steps: 1, building slow-time random complex envelope sequences of each point target at a plurality of junction radars; 2, estimating the mean power of each point target at each junction radar; 3, enabling the slow-time random complex envelope sequences of the same point target at the plurality of junction radars to be combined in a paired manner to form a plurality of envelope groups, and estimating a correlation coefficient; 4, selecting the real part of the correlation coefficient of each envelope group as the correlation tolerance; 5, calculating the detection threshold of the correlation tolerance corresponding to each envelope group; 6, judging whether the correlation tolerance is greater than the detection threshold or not: judging that the envelope groups pass through false target examination if the correlation tolerance is not greater than the detection threshold, or else, marking two corresponding point targets as false targets; 7, eliminating the false targets.

The invention discloses a frequency domain and space domain joint anti-interference method aided by probability search. The method includes the first step of signal preprocessing, the second step of frequency domain processing and the third step of space domain processing, wherein in the first step, signals are finally divided into I-path signals and Q-path signals to be output; in the second step, the I-path signals and the Q-path signals finally output in the first step are divided into two branches to be processed, and then the delayed signals and the obtained signals are synthesized through an adder; in the third step, space domain power inversion self-adaptive filtration is performed on the output signals finally synthesized in the second step, broadband interference in the signals is suppressed, and final output signals are obtained. The method solves the problem that when the frequency domain and the space domain are combined to resist interference, narrowband interference is drowned in broadband interference, and the performance of an anti-interference algorithm is reduced or the anti-interference algorithm fails, and the application range of the frequency domain and space domain joint anti-interference algorithm is expanded.

The invention discloses a method for automatically selecting ground control points during the interference measurement of a synthetic aperture radar. The method comprises the steps of randomly selecting two images in a multi-time-sequence SAR SLC image sequence to be subjected to interference measurement to form an interference pair, obtaining an interference graph through interference phase calculation, and calculating a coherence coefficient graph; segmenting the interference graph according to the number of required GCPs, figuring out an interference phase derivative of each pixel in the interference pair, carrying out statistics on the variance of all interference phase derivatives in each pixel local window, and searching a region in each block to form a candidate subset S1 of GCPs, wherein all searched regions are stable in interference phase or continuously and uniformly changing in interference phase; on the basis of the coherence coefficient graph, screening out pixels high inboth own coherence coefficient and coherence coefficient in the pixel local window, and forming a candidate subset S2 of GCPs; obtaining the intersection set of the candidate subset S1 and the candidate subset S2 of GCPs and obtaining a preliminary GCP selection result; optimizing the preliminary GCP selection result according to the number and the distribution of GCPs, and obtaining a final GCPselection result of GCPs. According to the invention, the method has an important value for improving the automation degree and the precision of the radar interference measurement of different modes.

The invention belongs to the field of the anti-interference research of a satellite navigation receiver, and especially relates to a satellite navigation anti-interference apparatus based on the memory matrix quasi inversion and an anti-interference method therefor. The satellite navigation anti-interference apparatus based on the memory matrix quasi inversion includes an array antenna module, a radio frequency channel module, an A / D converter module, a digital down conversion module, a memory matrix calculation module, a memory matrix quasi inversion module, a digital wave beam formation module, a digital up conversion module, and a D / A converter module. The invention provides an algorithm of the memory matrix quasi inversion, and improves the operation speed and precision by using the floating number operation. The weight is more accurate, and a Signal to Interference plus Noise Ratio (SINR) is improved. When the interference signal types, the interference signal strength, and the interference signal orientation change, the satellite navigation anti-interference apparatus based on the memory matrix quasi inversion and the anti-interference method therefor can fast and adaptively calculate the weight and inhibit the interference signals.

The invention provides an anti-interference method for a millimeter-wave anti-collision radar. The anti-interference method comprises: S1, generating a set of pseudo-random two-phase codes according to a radar transmission signal and carrying out two-phase encoding on the phases of all periods; S2, demodulating a radar receiving signal by using a transmitting modulation rule; S3, carrying out two-dimensional FFT processing on the demodulated result; and S4, carrying out CFAR detection processing according to the two-dimensional FFT processing result, thereby filtering an interference signal. According to the invention, a problem of the wrong target determination caused by the mutual interference between radars is solved; and the practicability and accuracy of the millimeter-wave anti-collision radar in a complex environment are improved. The less system resources are occupied; the method is flexible and is easy to implement; and the support is provided for the follow-up system upgrading and application extension. Therefore, the method has the great practical value and promotion value.

The invention discloses an adaptive anti-interference method for a satellite navigation system based on 2-norm multi-target optimization, and the method comprises the following steps: 1, constructing a direction vector and a constraint condition; 2, simplifying the constraint condition; 3, constructing a multi-target optimization anti-interference criterion; 4, solving the optimal solution to the multi-target optimization anti-interference criterion. According to the invention, a 2-norm matrix optimization function which enables the antenna gain in all directions to be constant is added to a single optimization function of a conventional blind anti-interference algorithm, thereby enabling an original optimization problem to be converted into multi-target optimization from single-target optimization, enabling the antenna gains in all directions to tend to be constant, and solving the problems that a directional diagram null steering opening is large in width in the blind anti-interference algorithm and the gains in non-interference directions are not flat.

The invention discloses a positioning method and system of a fiber distributed vibrating sensor based on a Sagnac interference theory. The system comprises a wavelength or frequency tunable laser, a Sagnac ring composed of optical fibers, a detector and a signal processing module. The method comprises the following steps that: the Sagnac interference ring composed of the optical fibers is arranged close to a to-be-detected point as a sensing element to perform real-time monitoring; when vibration happens, the light emitted by the tunable laser is injected into the Sagnac ring by a coupler; two beams of lights which have different frequencies and carry vibrating position information transmit clockwise and anticlockwise respectively in the Sagnac ring simultaneously and meet at the detector end; the interference output electrical signal is received by the detector and vibration positioning is performed according to the relation between the output signal and the vibration position. The single light supplier, the single optical fiber and the single detector are adopted to replace the complex structure of multiple light suppliers, multiple optical fibers and multiple detectors of the traditional positioning systems, thus the system is simpler and easier to realize. The system is applicable to safety early-warning for long-distance and large-area important safety territory.

The invention relates to interference photoelectric sensing smoke and fire detection method and device. The method includes: a. the light from the light source is divided into two beams with an optical splitter, one beam is emitted to the oscillation reference reflecting mirror, another beam is emitted to the target smoke sensing part; the scattering light generated by smoke and reflected light from the reference reflecting mirror are returned to the splitter to be superposed and carries on interference, and generates interference light signal; b. receives the interference signal with the photoelectric detector, and it is converted into interference photoelectric signal; c. the signal processing and analyzing device receive the interference signal, amplifies and processes them, judges if there has scattering light signal form fire smoke. The invention uses optical interference theory, upgrades the detection signal-to-noise ration and flexibility; the device needs not detection chamber and smoke absorbing device, it can be put into the open space to be detected, it can realizes the early detection to fire. The interference signal can be transmitted in fiber.

The invention relates to an earthquake data power frequency interference automatic identification and suppression method based on principal component analysis. The method comprises the steps of through calculating of average energy values of all paths of earthquake records, automatically identifying power frequency interference paths according to difference of the average energy values, extracting several adjacent paths including interference paths to form an earthquake interference path set, and using a principal component analysis technology to reconstruct feature vectors according to strong correlation of power frequency interference noises so that the purpose of suppressing the power frequency interference can be achieved. Since the principal component analysis is introduced, denoising is achieved, and the energy of effective signals is weakened at the same time, for this purpose, the amplitude-keeping processing is conducted on reconstructed data, and the path consistency of the earthquake records is guaranteed. As is proved, through the earthquake data power frequency interference automatic identification and suppression method based on principal component analysis, automatic identification and suppression on power frequency interference in earthquake data can be achieved, the quality of the earthquake data is effectively improved, and the earthquake data power frequency interference automatic identification and suppression method has important significance particularly in repairing destroyed paths of original earthquake records caused by the power frequency interference.

The invention provides a novel HOM interference theory based gravity instrument. The instrument comprises an entangled source (1), a delayer (2), a first beam splitter (3), a stress sensor (4), a prism (5) to be dropped, a reference prism (6), a second beam splitter (7), a first detector (8), a second detector (9), a coincidence measurement logic calculator (10), an atomic block (11) and a controller; when in use, the delayer (2) is adjusted to delay to enable destructive interference between the idle light and signal light flowing through the initial position, then the prism (5) to be dropped freely falls down to the end position, the free falling time is recorded, the delayer (2) is adjusted to delay again to enable destructive interference between the idle light and the signal light flowing through the end position, and finally the gravity acceleration can be obtained through the controller according to the difference between two delay, and the difference between the initial time and the end time. According to the instrument, the HOM interference theory is utilized to achieve the high precision measurement of the gravity accelerator; the instrument can be widely applied to the fields of metering, surveying and mapping, physical geography, ocean exploration and space science.

The invention provides an anti-cheating interference method based on bionic combined navigation assistance; the method comprises the following steps: using bionic combined navigation to obtain carriernavigation information in real time through multi-source data fusion, combining said information with a satellite ephemeris in a satellite navigation message, and calculating to obtain anti-interference detection auxiliary information; carrying out cheating interference detection on a GNSS baseband signal processing portion, detecting, identifying and removing cheating interference signals; detecting message time delays on a GNSS information processing portion, detecting whether regenerative cheating interferences exist in the cheating interference or not; carrying out cheating detection again on a GNSS positioning resolving portion, and detecting, identifying and removing cheating interference signals. The method can obtain navigation information without being affected by external environments, uses the bionic combined navigation assistance information to effectively determine whether cheating interference signals exist or not, thus detecting and preventing cheating interferences, enlarging the suitability of an anti- cheating interference algorithm, and improving the system reliability.

The present invention discloses a miniature fiber high temperature sensor based on the Michelson interference theory and a production method. The sensor is formed by a fiber (1). The core of the fiber is split into two parts, one part is provided with a planar reflecting surface (5) at an end part, and the other part is provided with a 45-degree reflecting surface (6) at the end part. When one light beam is emitted to the end face along the fiber core (3), the light beam is split into two beams, wherein one beam is reflected by the planar reflecting surface (5) to form reflection, one interferometer arm of a Michelson interferometer is formed, the other beam is fully reflected by the 45-degree reflecting surface (6) and then is reflected by a fiber wall reflecting surface (4) again, the other beam is coupled back to the fiber core (3), and the other interferometer arm of the Michelson interferometer is formed. The two beams meet at the fiber core to form Michelson interference fringe. Compared with the traditional Fabry-Perot or mach-zehnder temperature sensing, the miniature fiber high temperature sensor and the production method have the advantages of theoretical innovation, simple structure, reliable performance, and low production cost.