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3results about How to "Downsampling" patented technology

A differential coupled single frequency time varying low quantification imaging method

PendingCN122260321ASuppress nonlinear quantization harmonicsReduce imaging background noise floorRadio wave reradiation/reflectionChannel dataImaging processing
The application belongs to the technical field of radar signal processing and imaging, and provides a differential coupling single-frequency time-varying low-quantization imaging method, which comprises receiving a SAR echo signal, constructing a single-frequency time-varying threshold signal, single-bit quantization processing of a reference channel, single-bit quantization processing of a phase shift channel, double-channel data fusion and harmonic cancellation, and imaging processing based on a synthesized signal. The application effectively reduces the quantization noise base and improves the detection capability of a SAR system on weak targets under the premise of not significantly increasing the hardware cost.
Owner:SHENZHEN UNIV

Terahertz hyperspectral image restoration method and system based on low-rank joint sparsity

PendingCN121961934AOvercome detail lossOvercome Artifact DeficienciesImage enhancementImaging qualityObservation data
The invention discloses a terahertz hyperspectral image recovery method and system based on low-rank joint sparsity, and mainly solves the problems that in the prior art, a terahertz hyperspectral image recovery method adopts a single primary function for representation, detail loss and artifacts are easily caused, and the imaging quality is poor in a low sampling rate or low signal-to-noise ratio environment. According to the implementation scheme, the method comprises the following steps: sparsely acquiring a terahertz hyperspectral image of an image domain to obtain actual observation data; defining a sparse forward transformation operator and a sparse inverse transformation operator by using multiple groups of wavelet bases and Dirac bases; the method comprises the following steps: constructing a terahertz hyperspectral image recovery model based on low-rank joint sparse constraint by using actual observation data and a sparse forward transformation operator, and solving the image recovery model by using a primal-dual splitting method to obtain a recovered terahertz hyperspectral image. The terahertz hyperspectral image recovery method realizes high-resolution terahertz hyperspectral image recovery in an extremely low sampling rate or low signal-to-noise ratio environment, and can be used for medical auxiliary diagnosis, security check screening and drug detection.
Owner:XIDIAN UNIV

Low-power-consumption geomagnetic vehicle detection method and system

The invention discloses a low-power-consumption geomagnetic vehicle detection method and system. The method comprises the following steps: acquiring triaxial geomagnetic data; performing first-order difference and filtering on the three-axis data to obtain a smooth first-order difference signal; in a vehicle-free state, a mean value and a standard deviation are obtained through calibration, a Gaussian probability density function is established, an integral interval is constructed based on a deviation amount, a single-axis condition probability item is calculated through integration, and three-axis fusion is performed in combination with a state-related correlation correction coefficient to obtain a vehicle existence probability; in a state machine model including no vehicle, arrival detection, delay confirmation, and vehicle passing and leaving detection, outputting a vehicle arrival moment and a vehicle leaving moment according to a vehicle existence probability, a hysteresis threshold, a continuous point criterion and a delay confirmation mechanism, and compensating and correcting group delay introduced by filtering; and reporting detection information when the vehicle arrival event or departure event is output. According to the method, low power consumption and baseline drift resistance are both considered under the condition of a relatively low sampling rate, and the vehicle detection robustness is improved.
Owner:XIDIAN UNIV