Identification of Key Parameters for Remaining Useful Life Prediction of Radar T/R Module Using Least-Squares Method

The failure of radar sensors during military operations could result in false positives or negatives for intruder detection. The predictive life cycle estimation of electronic components in radar is an important topic. However, due to the sensitivity of radar to thermal noise from monitoring circuits, it is difficult to monitor its electronic components of radar for fault detection. Using statistical information of past events of faulty Transmit/Receive (T/R) modules of large phased array radars (LPAR), this paper identified parameters responsible for the degradation of radar subsystems. From historical data, relationship between 17 monitoring parameters and 3 fault categories is determined using least-squares (LS) method. A set of weight coefficients obtained by LS method is used to represent the relationship, and key parameters that contributed majorly to each fault category are examined. Using simulation, faults are injected into the identified parameters, and fault degradation level of the T/R module is estimated using linear degradation model. The proposed prediction method has lower average prediction error compared to index similarity-based prediction method for two fault categories (fault 1 and 2).