51results about How to "Improve detection performance" patented technology

The invention discloses a method for detecting a base station feed system on line, a base station system and an antenna suite. The base station antenna system comprises antenna test accessories which are arranged at antenna fixed positions and are used for fixing test terminals; the antenna test accessories comprise fixed test positions which are used for arranging the test terminals and making the direction of polarization of transmitted signals relatively fixed with the direction of polarization of a base station receiving antenna when the test terminals are at the fixed test positions; and the output characteristics of the base station receiving antenna are fixed in a preset error range. By the method, the performance for detecting the feed system is improved; the online performance detection can be immediately and conveniently performed on the whole base station system after the project installation of the whole base station system is completed; and that the base station feed system is in a bad condition can be instantly found and immediately improved to ensure that the base station system for project delivery meets the requirement on design performance.

The invention discloses an approximately optimal radar target detection method against K-distributed clutter plus noise and aims to solve the problem that the prior art is not completely suitable for target detection against K-distributed clutter plus Gaussian white noise. The method comprises steps of: 1) acquiring an echo data matrix, and blocking the echo data matrix; 2) selecting a to-be-detected distance unit zk of the bth echo data block, and calculating the covariance matrix estimator R<k> of the to-be-detected distance unit zk; 3) calculating the carrier noise ratio CNR of the echo data by use of the covariance matrix estimator R<k>; 4) calculating the test statistics xik of the to-be-detected distance unit by use of the CNR and the R<k>; 5) calculating the detection threshold T<xi> according to the false alarm probability; and 6) judging whether the a target exists or not by comparing the size of the test statistics xik and the detection threshold T<xi>. In this way, the target detection performance is improved and the approximately optimal radar target detection method can be used for radar motion detection under the back ground of sea clutter.

The invention discloses a spectrum sensing algorithm based on variational mode decomposition, and solves the problem that a signal at a receiving end is interfered by a noise background in the prior art. The method comprises the following steps of: 1, generating a simulation signal BPSK; 2, taking the mean value of the instantaneous frequencies of the components as a decomposition parameter, determining an optimal mode decomposition number K according to a change curve of the decomposition parameter, and setting an appropriate penalty factor alpha; 3, performing variational mode decompositionon the BPSK signal according to the obtained decomposition parameters; 4, respectively carrying out power spectrum estimation on the obtained L intrinsic modes; 5, taking the ratio of the sum of the spectral line intensities of the intrinsic modes to the sum of intensities of all the intrinsic modes as a test statistic; and 6, comparing the obtained test statistics with a judgment threshold, and making a final judgment. According to the method, the equivalent band-pass filtering characteristic and the Wiener filtering structure of variational mode decomposition are utilized, frequency bands are better divided, and denoising processing is better carried out; and compared with a traditional power spectrum segmented cancellation algorithm, the detection performance can be remarkably improved.

The invention relates to an electrochemical sensor for detecting lead. The electrochemical sensor comprises a glassy carbon electrode, wherein the glassy carbon electrode is utilized as a working electrode in a tri-electrode system, the surface of a detection end of the glassy cabon electrode is modified by a multi-walled carbon nanotube, nano golden particles are deposited on the multi-walled carbon nanotube, and a sulfydryl-modified capturing probe is connected with the nano golden particles; the electrochemical sensor further comprises an aptamer probe, wherein the aptamer probe and the sulfydryl-modified capturing probe are complementally paired to form a double-chain structure. According to the electrochemical sensor for detecting the lead, the aptamer probe is utilized to cover lead ions so as to be separated from the capturing probe, and during the separation, an electrochemical signal to be detected is generated, so that the purpose of detecting the content of the lead ions in the water body is achieved; the electrochemical sensor has the advantages of high sensitivity, excellent selectivity and stability, and the like.

The invention provides a resource configuration method, an information sending method, a base station and a terminal. The resource configuration method is applied to a first base station to which a first cell belongs and comprises the steps of: acquiring configuration parameter information for optimizing the configuration of a physical random access channel resource of the first cell, wherein theconfiguration parameter information comprises resource configuration information about a MulteFire short physical random access channel (MF-sPRACH) of an adjacent cell of the first cell and/or randomaccess channel (RACH) information about the first cell; and configuring the physical random access channel resource of the first cell according to the configuration parameter information. The resourceconfiguration method, the information sending method, the base station and the terminal improve the preamble detection performance of the cell, and improve the success probability of cell random access.

The invention relates to a daytime celestial body detecting device, which is characterized by mainly comprising a light shield, a symmetrical turn-back type optical system, an eight-shift light filterturntable, a linear polaroid turntable, a CCD camera and a corresponding mechanical structure. The daytime celestial body detecting device adopts a spectral filtering method and a polarization methodto detect target celestial bodies under a daytime cloudless sky background while having novelties, and improves the performance of detecting the daytime celestial bodies.

The invention relates to a radar maneuvering target fast fine processing method based on graded accumulative detection, and belongs to the technical field of the radar signal processing and detection.The method comprises the following steps: firstly performing Fourier transform, comparing with a primary threshold under a high-false alarm probability condition, and then performing fractional Fourier transform and fractional ambiguity function operation on a distance unit echo after exceeding the threshold in parallel, selecting the optimal transform domain corresponding to the large output signal to clutter ratio to form the distance-optimal transform domain two-dimension data; regarding the amplitude thereof as the detection statistics, comparing the detection statistics with the primarythreshold under the low-false-alarm probability condition and judging, thereby accomplishing the maneuvering target detection. The processing is performed only in a few distance units exceeding the primary threshold, thereby reducing the operation burden while guaranteeing high detection performance; multiple movement parameters of the maneuvering target can be accurately estimated, such as speed,acceleration and jerk, and the fast fine processing of the maneuvering target is realized.

The invention discloses a cooperative spectrum sensing method based on double-threshold energy detection. The method includes the steps of performing double-threshold local determination on data perceived by a perception user locally, determining a frequency band to be occupied if the data is greater than the maximum and sending Presence to a data center, determining the frequency band to be idle if the data is smaller than the minimum and sending Absence to the data center, and packing and then sending statistics and the signal to noise ratio to the data center if the data is smaller than the maximum and greater than the minimum; storing the received statistics and the received signal to noise ratio in the data center, directly determining the frequency band to be occupied if the data center receives any one of Presence, reading the statistics and the signal to noise ratio of every perception user if the data center does not receive any Presence, utilizing the maximal-ratio combining principle to obtain the weighting factor of every statistic for further obtaining statistics after combination, and performing single-threshold cooperative spectrum sensing on the statistics after combination. The cooperative spectrum sensing method based double-threshold energy detection can detect whether different frequency bands are idle or not, is applicable to different noise environments, dynamically sets a soft decision threshold and improves the detection performance of a system.

The invention discloses a radar signal adaptive detection method based on an autoregressive model. According to the concept, a radar receives coherent pulse sequences of N pulses, the coherent pulse sequences of the N pulses serve as to-be-detected unit echoes z0 of a target, and then a target detection problem of the radar is represented by a binary hypothesis test, wherein H0 indicates that z0 only has an interference hypothesis, H1 indicates that z0 has target and interference hypotheses, and first-order partial derivatives of a joint probability density function f(z0, ZK/theta) of z0 and ZK on two-dimensional column vectors theta r of a target amplitude, an upper left block matrix of a Fisher information matrix J(theta) inverse of a to-be-estimated parameter theta, the maximum likelihood estimator of variance sigma<2> of white complex Gaussian noise and the maximum likelihood estimator of an autoregressive parameter vector a of the M-order autoregressive model are calculated respectively; the detection threshold eta AR-Rao of the autoregressive model based on the Rao detection method is set, and a target detection expression TR, based on the autoregressive model, in z0 is calculated; if the TR is larger than eta AR-Rao, a target exists in z0; otherwise, the target does not exist in z0.

The invention discloses a large-scale MIMO (Multiple-Input Multiple-Output) detecting method and belongs to the technical field of wireless communication. The large-scale MIMO detecting method comprises the steps of detecting an MIMO signal by utilizing a BP (Belief Propagation) based iterative algorithm in a real number domain; before BP iteration, firstly normalizing and quantifying all the definitive variables to enable the variables to be within a range of [-1, 1], and then representing the normalized and quantified definitive variables by using random bit streams with symbols; in the BP iteration process, finishing updating and delivery of information through random calculation; and after the BP iteration is finished, converting the random bit streams output after iteration into the definitive variables to serve as output soft information. The invention also discloses a large-scale MIMO detecting device. By combining the BP algorithm in the real number domain with random calculation, the hardware consumption and system delay just increase linearly along with the addition of the number of transmitting or receiving antennas while the detecting performance as same as that of definite detection is guaranteed, and accordingly the large-scale MIMO detecting method and device can well adapt to large-scale MIMO scenes.

The invention discloses a multichannel measurement information configuration method based on space grid data alignment. The method is characterized by carrying out space grid division on a space monitoring space, calculating pitching-orientation-distance information of each space grid corresponding to each radar by utilizing geometrical relationship between space grids and radars, recording mark numbers of the grids and establishing a grid retrieval matrix; then, determining a scanning irradiation mode of a wave beam, and enabling the grid retrieval matrix to be in one-to-one correspondence with the irradiation modes to obtain a two-dimensional grid-mode retrieval matrix; and finally, mapping the pitching-orientation-distance information of the space grids into a local grid information data retrieve table based on mode mark numbers, extracting a detection unit corresponding to each grid according to the grid data table and serving measurement accumulation corresponding to each channel detection unit as detection statistics amount and carrying out detection on a monitoring plane.

The invention discloses a full coherent full polarization MIMO radar four-channel integrated target detecting method, which is used to solve a problem of a conventional non-coherent accumulation detector that detection performance is lowered, when signal-to-noise ratios of echo signals of four polarization channels are different. The full coherent full polarization MIMO radar four-channel integrated target detecting method comprises steps that 1) a full coherent full polarization MIMO radar is used to transmit signals, the waveforms of which are orthogonal to each other, by orthogonal polarization channels; 2) the full coherent full polarization MIMO radar is used to receive the echo signals by the orthogonal polarization channels; 3) the four-way pulse compression of the echo signals received by the orthogonal polarization channels is carried out, and the echo signals of the four polarization channels are acquired; 4) the signal-to-noise ratio weighting integrated detection of the echo signals of the four polarization channels is carried out. Compared with the prior art, the full coherent full polarization MIMO radar four-channel integrated target detecting method has constant false alarm performance, and the better detection performance is also provided, and therefore the full coherent full polarization MIMO radar four-channel integrated target detecting method can be used to realize the target detection of the full coherent full polarization MIMO radar under a noise background.

The invention provides an access grade inspection method and device. The method comprises the steps that according to terminal state access grade prohibition information and the member state of a terminal in a cell, relevant terminal state access grade prohibition parameters are determined; and according to the determined relevant terminal state access grade prohibition parameters, access grade inspection is carried out. The access grade inspection method and device solves the problem that in the relevant technology, the effect that member user equipment (UE) has higher access priority compared with non-member UE can not be guaranteed, therefore the access grade inspection effect is improved, and user experience can be improved.

The invention provides a target detection method combined with a lightweight network, and aims to solve the problem of balancing the detection speed and precision of a small target such as UAV, realize the lightweight of a network model, and provide possibility for target detection on an embedded platform. According to the characteristics of small size, high flight speed and the like of an unmanned aerial vehicle, the invention provides a quick target detection algorithm improved in combination with a lightweight network. The YOLOv3 algorithm for detecting three feature scales is expanded to five feature scales for detection, and the detection performance of small target scenes such as unmanned aerial vehicles is improved. A lightweight feature extraction network is constructed in combination with a Ghost module in a lightweight network, and in order to further improve the detection performance of the network, a channel attention mechanism is added to suppress unfavorable information. According to the invention, a UAV data set of an urban background is generated for training. Experimental results show that the method provided by the invention can effectively improve the detection precision of the UAV under the complex city background and meet the real-time requirement.

The invention discloses an energy detection method based on a double-threshold power spectrum double-average ratio, and relates to the technical field of cognitive radio, and the method comprises thesteps: 1, calculating double thresholds and a detection statistics TDTED under double-threshold energy detection, judging whether the detection statistics TDTED is greater than a lower threshold gamma0 and less than an upper threshold gamma 1 or not, and if not, executing the step 2; if so, executing the step 3; 2, judging whether the detection statistics TDTED is greater than or equal to an upper threshold gamma 1 or not, if so, determining that the PU signal exists, and if not, determining that the detection statistics TDTED is less than a lower threshold gamma 0, and determining that the PU signal does not exist; 3, calculating the maximum value and the minimum value of the power spectrum, the test statistics TDPSRA and the threshold value gamma DPSRA by adopting a power spectrum double average ratio algorithm; and 4, judging whether the test statistics TDPSRA is greater than or equal to a threshold gamma DPSRA, if so, determining that the PU signal exists, and if not, determiningthat the PU signal does not exist. According to the invention, another detection algorithm for processing is added between double thresholds, so that the processing efficiency of the algorithm is improved, and the detection performance of energy detection can be remarkably improved.

The invention discloses an FDA-MIMO radar incremental distance-angle two-dimensional beam forming method, which aims to realize accurate estimation of the distance of a target in each distance gate and improve the target detection performance. The method comprises the following steps of 1) acquiring a transmitting signal of an FDA-MIMO radar transmitting array element, 2) obtaining a receiving signal of a receiving array element after frequency mixing of a radar receiving end, 3) performing matched filtering on the transmitted waveform to obtain a sampling signal, 4) calculating a receiving signal vector after matched filtering of the radar receiving end, and 5) constructing a virtual steering vector according to the received signal vector, and finally obtaining an incremental distance-angle two-dimensional beam forming directional diagram. According to the method, the MIMO technology is adopted for the FDA array, joint beam forming is carried out at a receiving end, distance and angle decoupling is achieved, an antenna directional diagram dependent on the angle and the distance at the same time is generated, and incremental distance-angle joint detection and interference suppression of a target are achieved in a distance-angle joint domain.

The invention belongs to the technical field of airborne early warning radar ground moving target detection, and discloses an optimal rear Doppler clutter rejection method for a reconstructed reference channel. The optimal rear Doppler clutter rejection method comprises the steps of performing sliding window processing on the pulse data of each receiving channel in time domain by aiming at each distance unit; performing azimuth Fourier transform on the corresponding data of each receiving channel after the sliding window processing; performing time domain combination by aiming at a first receiving channel, and then uniting the data of other receiving channels to construct the corresponding data vectors of all distance units; getting a covariance matrix and a clutter rejection weight according to an optimal matching guidance; and finally, performing clutter rejection on all distance units by using the obtained clutter rejection weight.

The invention provides a target detection method, model and device, a trajectory tracking method and device, and electronic equipment, and the method enables a target detected by the model to cover more receptive fields through improving the structure of a target detection model and adding a hole coding module, thereby improving the detection efficiency of a small-size target or a target in a low-resolution feature map, reducing the false alarm rate of target detection throughthe head prediction module, improving the precision of target detection in the video, and can be particularly applied to detection of small targets in the video.

The invention provides a novel and efficient decision feedback equalization algorithm applicable to an E-UTRAN uplink. The algorithm takes the traditional frequency domain decision feedback equalization algorithm as a basis, adds a loop detection mechanism, and greatly reduces error code transmission and improves the reliability of data transmission through a plurality of iterative feedback. In addition, the algorithm adopts hard decision in the course of iterative feedback, thus greatly reducing complexity; and the algorithm does not need to change the frame structure of the uplink in an E-UTRAN protocol and the transmitter structure of a system, and does not affect the effectiveness.

The invention discloses a working frequency optimization method in a radar tracking state, and belongs to the technical field of radars. The method is suitable for searching for a strong point of thesignal-to-noise ratio at a frequency response value and can improve the detection performance on a weak target and achieve the purpose of greatly reducing the radar transmission power on the premise that the detection probability required by a system is met by increasing the echo signal-to-noise ratio through frequency optimization. The idea of the method comprises the steps that a radar is determined, a target exists in the detection range of the radar, the frequency interval of a radar transmitting signal is determined, and then a frequency vector is obtained; output data of M frequencies are obtained according to the frequency vector, wherein M>=1; estimated target measurement data is obtained according to the output data of the M frequencies; a polynomial fitting function is obtained according to the estimated target measurement data; and the polynomial fitting function is solved by means of a function optimization method, and then a final radar working frequency is obtained, wherein the final radar working frequency is a working frequency optimization result in the radar tracking state.

The invention discloses a pedestrian detection network, which takes VGG16 as a basic network and comprises five characteristic layers, namely fc6, fc7, conv6 _ 2, conv7 _ 2 and conv8 _ 2. The invention also discloses a pedestrian detection network model training method. The method comprises the following steps: calculating an expected value E of the pedestrian frame width-to-height ratio; extracting features to obtain a confidence map and a coordinate bias map; making a dense frame generation strategy; preprocessing the training data file, and training a pedestrian detection network to obtaina pedestrian detection network model. The invention also discloses a pedestrian detection method, which comprises the following steps of: setting a detection threshold value, loading the pedestrian detection network model and initializing network parameters; sending the picture into a model to obtain a detection result; filtering all the detection frames through non-maximum suppression to remove the frames detected repeatedly, and finally storing the result in a file. The method is based on the dense frame generation network, effectively overcomes the defects of high leak detection rate and the like in a pedestrian dense scene in the prior art, and improves the detection performance of the frame in the pedestrian dense scene.

The invention discloses a damage detection system of long and thin composite material and detection method thereof. The damage detection system of the long and thin composite material comprise a measurement device for measuring modal shape of the long and thin composite material, a Fourier modal curvature computing module and a judgment module; the modal shape measurement device comprises a force hammer for knocking h measurement points uniformly distributed on the long and thin composite material at intervals, an acceleration sensor for measuring the acceleration of the measurement point and a modal shape measurement module; the modal shape measurement module connected with the acceleration sensor generates the modal shape (WX) based on the acceleration, the Fourier modal curvature computing module computes the Fourier modal curvature (w'x) through the formula (F1), the judgment module is connected with the Fourier modal curvature computing module, if the Fourier modal curvature (w'x) is greater than a predetermined threshold value, the judgment module judges that the measurement point with the Fourier modal curvature (w'x) greater than the predetermined threshold value is the damage position.

The invention relates to the technical field of target detection, in particular to an improved YOLOv3 minimum remote sensing image target detection method and device and a storage medium. According tothe invention, an additional bottom-up and transverse connection path is added to the FPN module to improve the performance of the low-resolution feature; a top-down and bottom-up feature pyramid network is constructed, a bidirectionally combined pyramid feature layer is fused and applied to target detection of a remote sensing image, the dimension of a network model is reduced by adopting 1 * 1convolution, and the detection speed of the network is improved. And finally, quantitative and qualitative comparative analysis is carried out on VEDAI and NWPU VHR remote sensing vehicle data sets and the most advanced YOLOv3 network. The result shows that the detection performance of the improved network is obviously improved compared with the original network, the detection speed of the networkis hardly changed, and the problems of low target detection rate, high false alarm rate and low detection speed of the minimum remote sensing image at the present stage are solved.

The invention discloses a cross-camera multi-target tracking method for a warehouse scene. The method mainly comprises three parts of target detection, multi-target tracking and trajectory mapping. The target detector achieve accurate detection under the scene that the targets are mutually shielded; the multi-target tracker can predict the position of each target in the current frame based on the target template frame; The method includes: updating a target state and tracking pool information by optimally matching the detection frame and the multi-target tracking frame; achieving cross-camera tracking of the target based on the appearance characteristics of the target by utilizing the space-time relationship between the cameras; and mapping the target trajectory to a unified warehouse map through a projection mapping technology so as to visualize the tracking process. According to the method, robust cross-camera detection and tracking in a warehouse scene can be achieved.

The invention relates to the technical field of target detection, in particular to a target detection method, system and apparatus for an object with a large length-width ratio, and a medium. The method comprises the following steps: acquiring a to-be-detected target image; inputting the to-be-detected target image into a trained target detection model, wherein a loss function of the trained target detection model comprises a length loss value of a long side of an object and a central position loss value of the long side of the object; outputting the position of each object in the target image and a plurality of category probability values; and determining a final category of each object according to the plurality of category probability values. According to the target detection method for the object with the large length-width ratio, the central position loss value of the long side of the object and the length loss value of the long side of the object are additionally added into the loss function, so that the model is guided to improve the detection performance of the object with the large length-width ratio, and the target detection precision and efficiency are improved.

The invention belongs to the technical field of signal processing, and relates to a linear detection method for signals in non-free space environment around a human body, which comprises the following steps of: preprocessing received wireless signals and beginning timing; performing primary detection on the received signals by using the conventional linear detection methods respectively, and taking a linear detection method with the priority for detecting a performance curve as a primary detection method; when an electrocardiosignal of the human body meets physical realization conditions, detecting the received signals by using the primary detection method as the optimal detection method, otherwise, detecting the received signals by using an energy detection method as the optimal detection method; and in the process of detecting the received signals by using the optimal detection method, detecting again when the posture of the human body is changed or the time of a timer is greater than a time threshold. The linear detection method effectively avoids the problem that a single detection method cannot treat various channel conditions, improves the efficiency of screening the detection methods, and improves the detection performance in the non-free space environment around the human body.

The invention discloses a centrifugal microfluidic detection device and a centrifugal microfluidic detection system. The centrifugal microfluidic detection device comprises a power supply module, a control module, a rotating module, a cracking module, a heating module, an imaging detection module, a visual color detection module and a chip tray; and the imaging detection module can perform imaging detection on a test strip cavity of the chip, and the visual color detection module can perform color detection and absorbance detection on a reaction cavity of the chip. According to the centrifugal microfluidic detection device, the imaging detection module is arranged, so that imaging detection can be realized; by means of the visual color detection module, color detection can be achieved, and absorbance detection can also be achieved. Therefore, the centrifugal microfluidic detection device can realize two optical detections at the same time, and compared with the prior art that only one optical detection can be realized, the universality is effectively improved; immunodetection and nucleic acid detection can be realized at the same time, and the detection performance is improved.

One or more embodiments of the invention provide a highway accident prediction method and system based on a gradient boosting tree model, and the method comprises the steps of carrying out the data cleaning of a collected traffic accident data set, carrying out the data preprocessing, carrying out the feature extraction of the processed data, obtaining a key variable for predicting the occurrence of an accident, constructing and training a dynamic accident prediction model in combination with a gradient boosting tree model, and inputting the online data into the trained dynamic accident prediction model to obtain an output predicted accident value. According to the embodiment, the accident number of the road section can be predicted through the real accident data details, the problem that an existing model cannot carry out refined prediction on traffic accidents is solved, imbalance of training data can be overcome, and the effects of improving the detection performance and particularly reducing the false alarm rate are achieved; and compared with a traditional method, the model can carry out more accurate prediction on the traffic accidents.

The invention relates to an end-to-end multi-view three-dimensional human body posture estimation method and system and a storage medium, and the method comprises the steps: loading a pre-trained two-dimensional human body posture estimation network, and enabling a picture of each current view to serve as the input of the network; generating a thermodynamic diagram through a two-dimensional humanbody posture estimation network, and taking the thermodynamic diagram as the input of an LSTM thermodynamic diagram time sequence information extraction network; inputting the thermodynamic diagram into an LSTM initialization thermodynamic diagram time sequence information extraction network and an LSTM thermodynamic diagram time sequence information extraction network according to the value of the time sequence step length T to obtain a cell state and a hidden state; feeding the obtained hidden state into a decoder network to obtain a decoded thermodynamic diagram; fusing the thermodynamic diagram and the decoded thermodynamic diagram to obtain a thermodynamic diagram Ht (p) fused with time and space information; sending the thermodynamic diagram Ht (p) into a soft-argmax linear algebraictriangulation network to obtain a 2D point position; and solving an overdetermined equation on the homogeneous three-dimensional coordinate vector, and adopting a differentiable DLT-SII algorithm toobtain a final three-dimensional human body posture estimation point.

The invention relates to a Webshell detection method based on image analysis, terminal equipment and a storage medium. The method comprises the following steps: S1, collecting a plurality of normal and abnormal Webshell samples; S2, according to the collected Webshell samples and the Opcode sequence and the Opcode frequency of the Webshell to be detected, generating a corresponding RGB image; S3, calculating the distance between the RGB image of the to-be-tested Webshell and the RGB image of each Webshell sample, sorting the Webshell samples according to the sequence of the distances from small to large, selecting the first N Webshell samples from the sorting result, judging the types of the first N Webshell samples, and taking the type with the maximum corresponding number as the type of the to-be-tested Webshell. According to the method, the malicious behavior of the Webshell is represented by the Opcode feature, the two-dimensional gray level image is generated by using the Opcode sequence, and then the RGB image is synthesized by combining the gray level image generated by the Opcode frequency, so that the malicious behavior of the Webshell can be represented more completely, and the detection performance is improved.