基于卡尔曼滤波的信息融合技术在区域化探异常综合评价中的应用探索

在地球化学综合异常评价中,首次使用基于卡尔曼滤波的信息融合技术,对具有复杂地质地貌特征的西藏恒星错测区1∶50000水系沉积物测量的异常数据进行综合异常评价解释,该方法是把测区的地球化学元素视为多个传感器,将各地球化学元素的异常数据利用集中式多传感器卡尔曼滤波算法进行信息融合,绘制了综合异常图,并对恒星错测区进行了综合异常评价。综合异常图显示结果表明,该方法不同于传统意义上对各单元素异常的机械叠合,基本上消除了无成矿意义上的假异常,而且使致矿异常更为集中,异常形态表现为圈闭良好的椭圆状或圆状,综合异常形态清晰,得到的异常与测区内发现和评价的矿产基本一致。这表明采用基于卡尔曼滤波的信息融合技术处理综合异常的方法较传统方法更行之有效。

Application and exploration of regional geochemistry anomaly synthetical appraisal based on information fusion technique of Kalman Filter

The geochemistry synthesis anomaly appraisal,using information fusion technique based on Kalman Filter at the first time is used to conduct synthetic anomaly appraisal explanation of exceptional data of 1∶50 000 hydrographic sediment in Hengxing Cuo area of Tibet with complex geology characteristics.Geochemistry elements in the study area are regarded as many sensors,taking each element anomaly to conduct information fusion using multi-sensor,drawing the synthesis anomaly picture,and taking the synthesis anomaly appraisal to Hengxing Cuo area.The synthesis anomaly picture indicates that this method is different from the traditional mechanical overlapping of each element,and clearing away the anomaly of non-mineral meaning but also concentrating the mineral anomaly.The anomaly form is well circled in an elliptical or a circular shape,synthetical anomaly form is clear,and the anomalies calculated using the method coincide with known mineral deposits in the study area.This indicates that the approach of information fusion based on the Kalman Filter is more effective than the traditional method.