Soil component data fusion method and system based on multichannel Kalman filtering

The invention provides a soil component data fusion method and system based on multichannel Kalman filtering, and relates to the technical field of soil component measurement. According to the method, firstly, based on the thought of numerical iteration, a method for calculating a true value through an adaptive weighted fusion algorithm is improved, a traditional mean value calculation method is replaced with an iterative median calculation method, and the method can effectively reduce fusion variance and can greatly reduce the influence of an abnormal value on a fusion value; secondly, when an agricultural multi-sensor system is processed by a Kalman filtering model, filtering divergence may be caused. According to the method, a double-layer fading memory exponential weighted filtering factor is constructed, filtering fusion of different sensors in the soil can be realized, a constant error covariance symmetric array can be ensured, and data filtering can be carried out for a long time. The improved multi-ch