89 results about "Data fusion center" patented technology

The invention discloses a cooperative spectrum sensing method of a cognitive radio network considering malicious nodes. The cooperative spectrum sensing method is characterized in that the nodes involved in cooperative sensing are subjected to cyclic spectrum sensing to obtain characteristics of spectrum resources of a master user; normally sensed nodes and maliciously sensed nodes report sensed information to a data fusion center through an orthorhombic common control channel; the data fusion center perform data fusion on the collected sensed information and calculate the false alarm probability of the false alarm probability according to the malicious attach pattern of the malicious nodes; a secondary user and the master user share the spectrum resources, build a optimizing model, determine the constraint conditions of the transmitting power and the sensing time, solve the built optimizing problem, and repeat the steps to make the obtained average value to be the sensed parameter of the spectrum sensing model. The cooperative spectrum sensing method is fast in calculation and strong in pertinence and universality, and can correctly select the optimizing sensing period and the signal transmitting power in the sensing environment with the malicious nodes.

The present invention relates to the field of communications. Disclosed are a broadband spectrum sensing method, a fusion center (FC), a sensing node (SN) and a computer storage medium. The method comprises: the FC obtaining statistical idle probabilities of all current primary user (PU) physical channels; based on a sequence of the statistical idle probabilities from large to small, assigning SNs used for detecting channel spectrums to the PU physical channels in sequence; using the SNs assigned to the PU physical channels to detect the channel spectrums for the PU physical channels; and based on channel spectrum detection results, determining status of the PU physical channels.

The invention discloses a vehicle-road cooperative bus accurate data fusion center system which is operated in a bus management control center. The functions of the system comprises fusing the positioning information uploaded by a bus and the differential grid data stored in the center to obtain a more accurate real-time position of the bus, calculating and issuing the distances to the adjacent vehicles on real time, uniformly timing all buses through the Beidou NTP time synchronization protocol to realize time synchronization, and sending the real-time bus position information of the corresponding route and high-precision position of a station parking area to a bus stop platform. The issued information, such as folk news and advertisement information, can be displayed on display terminalsof the bus and the bus stop as needed.

The invention provides a rainy season land slide deformation monitoring method and a rainy season land slide deformation monitoring system. A data integration center is used to acquire a displacement value and a speed value of a monitoring point of a current sampling time point according to a displacement sensor and a speed sensor, and is used to acquire displacement values and speed values of the previous one or two time point / s, and two given error covariance matrixes, and is used to acquire a measurement noise covariance matrix estimation value and a process noise covariance matrix estimation value of the current sampling time point according to the ordinal number of the current sampling time point and the above mentioned parameters. Kalman filtering of the displacement value and the speed value of the current time point can be carried out by adopting the acquired matrix estimation values, and then the optimal displacement estimation value and the optimal speed estimation value of the current sampling time point can be acquired. The displacement value and the speed value can be the displacement weighted average and the speed weighted average. The two covariance matrixes can be estimated according to the actually acquired displacement value and the actually acquired speed value, and are not given, and therefore the matrix estimation values are real, and the filtering result is accurate. The invention also relates to the rainy season land slide deformation monitoring system.

The invention discloses a Lora signal monitoring system and method for a multi-node software radio platform. The Lora signal monitoring system comprises a Lora signal monitoring part and a data fusioncenter part; the Lora signal monitoring part comprises a plurality of Lora signal monitoring nodes, and each Lora signal monitoring node comprises a radio frequency front-end processing module, a software radio platform hardware processing module, a signal data processing module and a monitoring node upper computer software module; and the data fusion center part comprises a cloud server module and a user application software module. A radio frequency front end is used for preprocessing the wireless signals, an energy detection and convolutional neural network modulation recognition algorithmis used for recognizing the LoRa signals, and the multi-node monitoring is deployed to upload the data to a data fusion center to judge whether the LoRa signals exist or not and estimate the parameters. According to the invention, the identification and parameter estimation can be carried out on the LoRa signal with the unknown frequency point information, and the probability of the LoRa signal detection is improved.

The invention discloses a collaborative information processing method and processing system suitable for networked operations. The method comprises the following steps: (A), when the radar of the combat unit normally tracks the target, the state information of the target is obtained by the radar processor of the combat unit and the estimation error of the state information is estimated; (B), for all combat units The state information and estimation error of the unit are calculated to obtain the fusion information and fusion error; (C), when each combat unit performs fire control calculation, if the combat unit normally tracks the target, the state information and estimation error of the combat unit are used. The error is used for fire control calculation. If the combat unit cannot track the target normally, the fusion information and fusion error distributed by the data fusion center are used for fire control calculation. The invention is easy to exchange information, can meet the requirements of networked combat modes such as cooperative detection / tracking and cross-fire unit control, and has the characteristic of high precision.

The invention discloses a blind collaboration spectrum sensing method based on a soft fusion strategy. The method comprises the following processing flows: firstly, a sampling module in each sensing node samples a receiving signal from the same monitoring channel to obtain a sampling signal corresponding to each sensing node; and then, each sensing node computes the estimation variance of the estimation power and the instantaneous power of the corresponding sampling signal; each sensing node uploads the estimation variance of the estimation power and the instantaneous power of the corresponding sampling signal to a data fusion center; the data fusion center computes the test statistics; and finally, the data fusion center realizes the spectrum sensing by comparing the test statistics withthe judgment threshold, and judges whether an authorized user signal is existent in the monitoring channel; the method disclosed by the invention has the advantage that the hidden terminal problem ofthe sensing node can be well overcome without knowing the authorized user signal and the priori information of a wireless channel, and the sensing performance of the spectrum can be effectively improved.

The invention provides a two-coordinate ship-borne radar signal level fusion method. The two-coordinate ship-borne radar signal level fusion method comprises the steps of preprocessing echo data of aplurality of radars of the same type in formation, then uniformly transmitting the preprocessed data to a signal fusion center, converting the preprocessed data into a uniform coordinate system through coordinate transformation, and then realizing non-coherent accumulation of echo data of a plurality of radar targets by utilizing an improved dynamic programming algorithm to realize effective detection of a weak target. According to the two-coordinate ship-borne radar signal level fusion method, the data volume transmitted to the data fusion center by each ship is greatly reduced, and the weaktarget detection performance is improved; the problems of low target parameter measurement precision and difficulty in multi-homotype radar signal level fusion cooperative detection space registrationcaused by huge data volume transmitted between each ship and the data fusion center in the formation and the energy diffusion phenomenon of a dynamic planning method are effectively solved; and a powerful technical support is provided for detection of the weak target in a complex sea clutter environment.

The invention relates to a method for selecting cognitive users in coordinated spectrum sensing. According to the method, under the condition that prior knowledge of the signal-to-noise ratio of the cognitive user is unknown, the every-order autocorrelation coefficients of received signals are calculated by all the cognitive users so as to obtain an autocorrelation matrix, then the parameter B capable of expressing sensing properties of the cognitive user is obtained through analyzing calculation of elements of the autocorrelation matrix, the parameter B is transmitted to a data fusion center by the cognitive users, the property difference index delta Bi between each cognitive user and the best property cognitive user is calculated by the fusion center, the users bad in property are kicked out, and the cognitive users participating in coordinated sensing are selected out according to the from-small-to-large rule of delta Bi. With the method for selecting the cognitive users, while the cognitive sensing property is guaranteed, the number of nodes of the cognitive users participating in the cooperated sensing is reduced, network loads are reduced, occupancy of resources of a system is reduced, and the transmission efficiency of the system is also improved.

The invention relates to a multi-sensor fusion system. The multi-sensor fusion system comprises multiple ZigBee-based wireless monitoring nodes; data of each wireless monitoring node are respectively connected to a data pre-processing unit; the data pre-processing unit is connected with a data fusion center; and the data pre-processing unit assigns a a probability value to data of each node; fusion of data of each sensor is carried out by using a preset fusion rule by the data fusion center, and a decision result is obtained according to a decision rule. According to different assigned probability values of sensor data, data of multiple sensors are fused, the final result is obtained according to different rules, all-round monitoring can be obtained, the system has the advantages of low cost, high flexibility, easy configuration, high reliability and the like, and performances of the whole system are improved.