The autonomous flight of unmanned aerial vehicle cannot be separated from navigation algorithm and guidance algorithm. The function of navigation algorithm is to measure and calculate the real-time motion state and position information of UAV, so all kinds of sensors are the necessary premise to realize navigation algorithm and the necessary input of navigation algorithm.
With the development of science and technology, more and more sensors are available and more types of navigation systems are available. Take aviation system as an example. Currently, the airborne navigation systems are available for equipment including inertial navigation system, GPS navigation system, Beidou navigation system, Doppler navigation system and Rolland C navigation system. Not to mention which navigation system is better than the other ones, it just has its own characteristics, advantages and disadvantages.
In general, we will use multiple navigation systems at the same time, because one system alone cannot meet the use requirements. However, two or more non-similar navigation systems can effectively reduce measurement errors and correct them by measuring unified navigation information and calculating state information. Take unmanned aerial vehicle as an example. Since inertial navigation and GPS navigation are complementary in performance, we often adopt the combination of inertial navigation and GPS navigation to design airborne navigation system, to achieve good navigation performance.
Integrated Navigation design algorithm
There are generally two ways to realize the integrated navigation system:
Loop feedback method
Loop feedback method adopts classical loop control method to suppress system error, so that each subsystem can realize complementary performance at the same time. For example, our common method of using accelerometers and gyroscope to measure information to design complementary filtering and calculate attitude angle belongs to this kind.
Optimal estimation method
The optimal estimation method refers to the method that uses Kalman filter or Wiener filter to estimate the system error and eliminate it from the perspective of probability statistical optimization.
The above two methods are to permeate and organically combine the information of each system, thus playing a complementary role. However, usually the error sources and measurement errors of each subsystem are random, so the optimal estimation method is generally better than the loop feedback method. At present, the main stream of design of integrated navigation is Kalman filtering method.
Here I will give you a preview, and I will introduce the specific process of the above two methods to realize navigation calculation in detail.
The basis of navigation system is sensor, and the design input of navigation algorithm is the data measured by sensor. So before starting the design of navigation system, we should first understand what sensors are commonly used in unmanned aerial vehicles? What is the measuring principle of these sensors? As we mentioned above, the common navigation mode of unmanned aerial vehicle is inertial navigation + GPS, so the common sensors on unmanned aerial vehicle are also developed based on those two. Inertial navigation generally includes three-axis accelerometer, three-axis gyroscope, three-axis magnetometer, together with GPS, constitutes the main body of Airborne Sensor. Besides, there are ultrasonic ranging sensor, laser ranging sensor, airspeed meter, barometer, vision sensor, etc.
Accelerometer is an inertial sensor, which can measure the acceleration of unmanned aerial vehicle in XYZ three-axis direction, and usually it can also measure the three-axis attitude of aircraft together with gyroscope. The disadvantage of accelerometer is that the signal is greatly affected by vibration, so shock absorption processing is required when it is used on aircraft, and filtering is also carried out after data acquisition.
When the aircraft is still, what the accelerometer measures is the gravitational acceleration, so in actual use, we all need to remove the value of the gravitational accelerator. In general, the measuring principle of the accelerometer can be regarded as a spring-mass model, but in fact, the measurement of the accelerometer is based on piezoresistive effect, piezoelectric effect, etc. The forces generated by these effects are compared with resistance. Voltage and capacitance values are output through corresponding amplifier circuits and filter circuits.
In addition, when the external force used in the unmanned aerial vehicle is far less than gravity, the accelerometer can also be used to measure the attitude angle, because when the aircraft inclines, the acceleration measured by the accelerometer under the body axis system is related to the attitude angle of the UAV and the value of gravitational acceleration, while the value of gravitational acceleration is known, we can calculate the attitude information of the unmanned aerial vehicle according to the magnitude of the three-axis acceleration (except the course).
There are many kinds of gyroscope, MEMS gyro, piezoelectric gyro, laser gyro, fiber optic gyro, etc. The prices of gyroscope vary greatly. Generally, MEMS gyroscope is used in small-sized UAV, which is based on the working principle of Coriolis force. Coriolis force generates linear moving objects relative to the rotating coordinate system, because Coriolis force is compared to the rotational angular velocity, the corresponding angular velocity can be calculated according to the capacitance change generated by Coriolis force.
Gyroscope sensor can monitor the angular velocity of three axes, so it plays a very important role in navigation system, generally used for calculating attitude angle. However, since the angle obtained by angular velocity integration drifts seriously with time, a single gyroscope cannot calculate the accurate angle value, it usually needs to be used together with accelerometer, and this is the performance complementation we mentioned above.
Magnetometer, as the name shows, uses different magnetoresistance or Hall effect to measure the magnetic induction intensity in space. According to the principle of Lorentz force, the intensity change of electromagnetic field will produce a change in Lorentz force, thus changing the capacitance in the circuit.
Magnetometer is generally not used separately but used together with accelerometer and gyroscope to calculate the attitude angle. However, if the unmanned aerial vehicle crosses a large area when flying, the normal use of magnetometer will be affected due to the difference of magnetic field intensity around the Earth. Therefore, dual GPS is used to measure course information in many cases.
In addition, magnetometer is very sensitive to permanent magnetic substances such as hard iron and soft iron. The change of surrounding magnetic field will affect the use of Magnetometer. It is said that magnetometer is most susceptible to interference of all UAV sensors. When we debug unmanned aerial vehicles, we often encounter the situation of course drift, most of which are related to improper operation of magnetometer. Therefore, if there is a better method to measure the course, it is also necessary to remove the magnetometer.
When you go to a unfamiliar place, you use the electronic map in your phone for directions, and one of the most important parts of locating is GPS. GPS satellites in the sky broadcast a certain position and time stamp in real time, at this time, GPS receivers on the ground will receive the information. Only when the number of satellites is greater than or equal to 4, positioning information can be generated.
Normally, GPS can only be used in an open space, and drivers will find that GPS signals will be lost when entering bridges and tunnels when using navigation. Therefore, when using GPS, we should try our best to stay in the area without shelter. In order to increase the measurement accuracy, the GPS used on the unmanned aerial vehicle will use the enhancement methods such as pseudo-pitch difference and RTK, which can significantly improve the positioning accuracy of the unmanned aerial vehicle.
The operation principle of barometer is to use atmospheric pressure to calculate the height. The barometer is also a sensor that is easily interfered by the outside world. When the temperature changes, the air pressure will also change. In addition, the air flow generated by the rotor working on the unmanned aerial vehicle will usually affect the measurement of the barometer. Therefore, if relative height sensors such as ultrasonic wave or laser ranging sensors are installed, we can replace the barometer scheme by using ultrasonic wave/laser range finder + GPS height.
06 Ultrasonic transducer
Ultrasonic wave is a kind of sound wave beyond the auditory frequency of human ears. Due to its good directivity and strong penetrability, it is widely used in ranging and speed measurement. The ultrasonic signal is sent out by the ultrasonic sensor, which is reflected by the object and then received by another ultrasonic sensor. Therefore, the distance to the object is half of the product of the propagation speed of sound wave and the time interval. The price of ultrasonic sensors is generally relatively cheap, but due to the slow transmission speed of acoustic waves, the data update frequency of ultrasonic sensors is relatively low and the measurement range is small, which are the shortcomings of ultrasonic sensors.
07 Laser ranging sensor
The principle of laser ranging sensor is basically the same as that of the ultrasonic sensor, but transmission method is different. The laser ranging sensor emits the laser source, and its propagation speed is time-fast. Therefore, the signal frequency is much higher than that of the ultrasonic sensor, and the price is also higher. Therefore, its disadvantages are also obvious, high price and short measuring range, except for those that can be scanned, which is more expensive.
08 Visual Sensor
Visual sensors refer to the use of cameras to obtain image information, and then determine the status information such as position and speed of the target or aircraft relative to the target according to the image information. The post-processing algorithm is very important for visual sensors, especially the development of deep learning algorithm, which has brought new vitality to the application of visual sensors in unmanned aerial vehicles. Recently, many researches on UAVs are based on vision, such as target tracking, obstacle avoidance, location, etc.
09 An airspeed indicator
Airspeed meter is usually used on fixed-wing UAVs, because their working principles are closely related to air speed, such as lift force, stall speed. The measuring principle of airspeed meter is to determine the dynamic pressure of airflow according to Bernoulli’s principle by measuring the total pressure and static pressure of airflow, and then calculate the airspeed.