Abstract
Aiming at the limitations of a single High Resolution Range Profile (HRRP) in recognition, this paper proposes a Time step Correlation-based Feature Fusion (TCFF) method. This method calculates the covariance matrix at the time step of the two features extracted by the two channels, and assigns different weights to the time step according to the strength of the covariance correlation for feature fusion. The experimental results on the simulated ship target HRRP dataset show that the feature fusion method can achieve better recognition performance than the single channel model. Compared with simple feature fusion such as element addition and element contacting, it can also achieve better recognition results.
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