**1. Introduction**

612 Advances in Wavelet Theory and Their Applications in Engineering, Physics and Technology

Williamson, C.H.K. & Roshko, A. (1988) *Vortex formation in the wake of an oscillating cylinder*,

Rotorcraft UAV (RUAV) has similar mechanical structure with helicopter. It can be operated in different flight modes which the fixed-wing UAV is unable to achieve, such as vertical take-off/landing, hovering, lateral flight, pirouette, and bank-to-turn. For these advantages, RUAV can be used in many fields where human intervention is considered difficult or dangerous (Napolitano et al., 1998). So it can perform the tasks such as regional surveillance, aerial mapping, communications relay, power-line inspection, aerial photography and precision load dropping, etc. RUAV has many advantages, such as small in size, low cost, simple operation and convenient transportation. Therefore, RUAV has broad application prospects, high demands, and advantages that the fixed-wing unmanned aircrafts and unmanned airship can not replace.

Integrated navigation system can give the movement information of the carrier, thus every UAV has an integrated navigation system. Because of the limitations of weight, volume, power supply and cost, there is no redundant navigation system in RUAV. RUAV does not have the emergency landing properties of fixed-wing aircrafts or airships in case of failures. Therefore, a failure in any part of a RUAV can be catastrophic. If the failure is not detected, identified and accommodated, the RUAV may crash. The use of wavelet transforms the situation of accurately localizing the characteristics of a signal both in the time and frequency domains, the occurring instants of abnormal status of a sensor in the output signal can be identified by the multi-scale representation of the signal (Dabechies, 1988; Isermann, 1984; Zhang, 2000). Once the instants are detected, the distribution differences of the signal energy on all decomposed wavelet scales of the signal before and after the instants are used to claim and classify the sensor faults.

In low cost and small size integrated navigation system, MEMS (Micro Electronic Mechanical System) inertial sensors are used widely. But MEMS inertial sensors, especially MEMS gyroscopes have large noise. It affects the calculation accuracy of angle rotation matrix, and will further affect calculation accuracy of other navigation data such as position, velocity, and angular velocity. In order to improve the calculation precision of position and angle, digital filter is required to reduce the noise of gyroscope. Commonly, we used

Application of Wavelets Transform in Rotorcraft UAV's Integrated Navigation System 615

The overall rotorcraft UAV control system comprises: the aerial vehicle platform, the onboard avionics control system, and the ground monitoring station. The UAV helicopter itself is able to operate with the independent control computer system and onboard sensors.

In order to navigate following a desired trajectory while stabilizing the vehicle, the information of helicopter's position, velocity, acceleration, attitude, and the angular rates should be known to the guidance and control system. The ServoHeli-20 RUAV system is equipped with sensors including IMU (Inertial Measure Unit), GPS and digital compass, to obtain above accurate information about the motion of the helicopter in association with

> Angular Rate Range: 100 / sec Acceleration Range: 4*g* Digital Output Format: RS-232

Position Accuracy (CEP): 1.5m Digital Output Format: RS-232

Pitch, Roll Angular Range: 40 Digital Output Format: RS-232

Update Rate: > 100 Hz Size: 76.2 × 95.3 × 81.3 mm

Weight: <640g

Weight: 20g

Weight: 92g

Update Rate: 10 Hz Size: 71.1 × 49.6 × 1.2 mm

Update Rate: 20 Hz Size: 15 × 42 × 8.8 mm

The picture of sensors in the avionics box is shown in Fig. 1, and their primary parameters

The flight computer installed in avionics box is a typical industrial embedded computer system, so-called PC-104 in the whole system is kept as compact and light-weight as possible. The PC-104 has the ISA or PCI bus which features a 108.2cm 115.06cm footprint circuit board. Our flight computer system consists of a main CPU board and some other peripheral boards such as DC-DC power supply board, 8-channel serial communication device and PWM generation board. The main CPU board has a Celeron processor at 400MHz with 256MB SDRAM, fully compatible with the real-time operation system such as QNX. Hard drive or other equivalent mass-storage device for booting and running an

operation system and storing useful sensor data is needed to the flight computer.

**Sensor PARAMETERS**

*IMU400 IMU* 

*Crescent GPS* 

*HMR3000 Compass* 

Table 1. Sensors parameters

**2.1.3 Processor and control system** 

are shown in Table I.

**2.1.2 Navigation sensors** 

environment.

Kalman filters to decreasing the random noise. And we need to build the mathematic model of sensors' errors. The MEMS gyroscope has random drift characteristics of weak nonlinear, non-stationary, slow time-varying. And it is sensitive to external environments such as vibration and temperature. The result of Kalman filter is often imprecision and even divergence, because of inaccurate drift error model of MEMS gyroscope. Wavelet transform has the characteristics of multi-resolution and time-frequency localization, and we do not need to build the mathematic model of sensor errors. So it is ideal for signal processing and analysis of MEMS gyroscope.

However, Synthetic data simulated by means of a computer using real flight data from ServoHeli-20 and ServoHeli-40 RUAV, which is designed and implemented by Shenyang Institute of Automation, have verified the effectiveness of the proposed method.

The following part of this paper is organized as follows. In Section 2, the fault detection approach based on the wavelet transform is established. The RUAV verification platform is introduced in Section 3. The integrated navigation system and the characteristic of inertial sensor are discussed in Section 4. Real RUAV flight fault detection experiments in manual mode are described and discussed in Section 5, and conclusions are given in Section 6.
