A Kalman filtering-based method for signal reconstruction in complex environments
A Kalman filter and complex environment technology, applied in the field of signal processing, can solve problems such as low efficiency and high computational complexity
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[0061] In order to have a further understanding and understanding of the structural features of the present invention and the achieved effects, the preferred embodiments and accompanying drawings are used for a detailed description, as follows:
[0062] In the daily complex environment, the signal measurement value is seriously polluted by noise, such as the noise is Gaussian noise, obeying the mean value is zero, and the variance is The Kalman filter-based signal reconstruction method in a complex environment described in the present invention can further simplify the coding process of compressed sensing and improve the reconstruction accuracy, such as figure 1 As shown, it includes the following steps:
[0063] The first step is to quickly compress the signal. Design sparse measurement matrix Φ M×N , to obtain the measurement value y by performing compression measurement in a complex environment. First of all, it is necessary to design a suitable compressed measurement m...
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