The car dead reckoning (DR) navigation system uses a gyroscope (gyro) to estimate the instantaneous heading of the vehicle. With this information plus the distance traveled, the navigation system can correctly determine the location of the vehicle, even if the satellite signal is blocked by a crowded urban environment or tunnel. A major challenge in using gyroscopes in DR navigation is that satellite signals can be lost for extended periods of time, with the result that the cumulative angular error is too large to accurately locate the vehicle. This paper presents a simple solution to this problem. This article refers to the address: http:// How DR navigation works Figure 1 shows the basic working principle of DR navigation. A gyroscope measures the rate of rotation of the vehicle in degrees per second. The angle representing the immediate heading of the vehicle is determined by calculating the time integral of the rate of rotation. Combined with the heading and driving distance, the position of the vehicle can be determined, as indicated by the red line in the figure. Figure 1. How DR navigation works When using a digital gyroscope, the integration rate can be expressed as the rate sample and the product of the sampling interval: Where ri is the rate detected by the gyroscope, n is the number of samples, and τ is the sampling interval. The angular error accumulated over time can be expressed as: Where ei is the rate error of each sample, n is the number of samples, and τ is the sampling interval. According to this formula, as the required integration time becomes longer, the cumulative error becomes larger as shown in FIG. 2. These rate samples (measured with an evaluation board with ADXRS810 high performance angular rate sensor) simulate a DR navigation system with a total of 3300 rate samples. The blue line represents the gyroscope rate sample; the red line represents the cumulative angle error. Obviously, the cumulative angular error becomes larger with time. Figure 2. Rate measured using the ADXRS810 evaluation board. (Note: Angle errors are not drawn to scale.) Reduce integration time with low pass filter (LPF) Traditional methods of reducing angular error have focused on reducing en, but today's digital gyroscopes have a very low rate error specification. For example, the sensitivity of the ADXRS810 is 80LSB/°/sec, the offset is ±2°/sec, and the impact resistance is 0.03°/sec/g. The space for improvement is limited. In addition, en's compensation algorithm is very complicated. Compared to other applications such as Electronic Stability Control (ESC), gyroscopes in DR navigation systems can operate for long periods of time, such as when a vehicle travels through a long tunnel, GPS signals are not lost. In DR navigation applications, longer run times can cause angular errors to increase. If the integration time can be shortened, the cumulative angle error can be significantly reduced. When the gyroscope does not rotate, the rate output is small, but the output is not zero due to gyroscope noise. The ADXRS810 has ultra-low gyro noise and ultra-high sensitivity, and it is easy to filter out noise in the digital domain by setting the corresponding threshold. This process is equivalent to low-pass filtering because the gyro rate noise is in the high frequency region compared to the rate output due to rotation. Figure 3 shows the LPF version of Figure 2, where all rate samples less than 1°/s are zeroed and therefore ignored in rate integration. The remaining integration time is considered to be the effective integration time, which is only about 16% of the total integration time. This can greatly shorten the integration time. As a result, the cumulative angle error is also significantly reduced, as indicated by the red line in the figure. Figure 3. Rate measured using the ADXRS810 evaluation board and digital LPF. (Note: Angle errors are not drawn to scale.) In practical applications, the steering wheel of the vehicle is generally at zero degrees. Therefore, the effective integration time of the gyroscope rate can be reduced by ignoring, as is done in the experiment shown in FIG. Figure 4 shows a gyroscope rate sample from a real on-board test. Driving in the tunnel for about 180 seconds requires a 180 second rate integration time. If the LPF process is not used, the accumulated error in 180 seconds may be as high as 4°, which is too large to properly determine the position of the vehicle in the tunnel. Using the LPF process, setting the threshold to 0.5°/sec, the effective integration time is shortened to 84 seconds, a reduction of about 53%. The cumulative error drops to approximately 0.5° as shown in Figure 5. When setting the LPF threshold, it can be determined according to the accuracy required by the specific application. Figure 4. Unfiltered on-board gyroscope rate samples. (Note: Angle errors are not drawn to scale.) Figure 5. Vehicle gyro rate samples after using LPF. (Note: Angle errors are not drawn to scale.) in conclusion Today's digital gyroscopes have excellent specifications, so there is limited room for improvement in performance. In vehicle DR navigation systems and other applications that require long integration times, it is a simple but effective way to improve the accuracy by setting the LPF threshold to reduce the integration time. The ADXRS810 high-performance, low-cost digital gyroscope uses ADI's new MEMS technology and is a good choice for automotive DR navigation applications. The gyroscope is available in an ultra-small package with low offset, low noise and high rate sensitivity. Chip-integrated temperature compensation technology eliminates the need for an external temperature sensor and simplifies the temperature compensation algorithm. Its high impact resistance and vibration resistance are of great significance for automotive applications.
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November 01, 2020