Complementary filtering is a frequency based method used to design data processing algorithms exploiting signals with complementary spectra. The technique is mostly used in sensor fusion architectures, but it may also be effective in the design of state estimators. In spite of its potential in several areas of robotics, the complementary filtering paradigm is poorly used as compared to alternative time domain methods. The first part of the paper aims at reviewing the basics of complementary filtering in sensor data processing and linear systems state estimation. The second part of the paper describes how to exploit the main ideas of complementary filtering to design a depth controller for an actuator redundant autonomous underwater vehicle (AUV). Unlike with alternative state space methods commonly used to address the design of control solutions for actuator redundant systems, the proposed approach allows to fully exploit the knowledge of frequency characteristics of actuators. Simulation results are reported to demonstrate the effectiveness of the proposed solution.