How can you improve the signal-to-noise ratio of automotive sensors?

1 Choose the right sensor

The first step to improve the SNR of automotive sensors is to choose the right sensor for the application. Different types of sensors have different characteristics, such as sensitivity, resolution, bandwidth, and noise level. You should select a sensor that matches the expected range, frequency, and accuracy of the signal you want to measure. For example, if you want to measure the speed of a wheel, you should use a sensor that can capture the variations of the rotational speed without being affected by the vibration or the temperature of the wheel.

2 Shield the sensor

The second step to improve the SNR of automotive sensors is to shield the sensor from external sources of noise. Noise can come from various sources, such as other electrical devices, radio waves, power lines, or nearby metal objects. To reduce the noise, you should enclose the sensor in a metal casing or a grounded shield that can block or divert the unwanted signals. You should also avoid placing the sensor near sources of heat, moisture, or mechanical stress that can alter its properties or damage its components.

3 Filter the signal

The third step to improve the SNR of automotive sensors is to filter the signal before processing it. Filtering is a technique that removes unwanted components from the signal, such as noise, distortion, or interference. There are different types of filters, such as low-pass, high-pass, band-pass, or notch filters, that can be applied depending on the frequency and shape of the signal and the noise. You should use a filter that preserves the essential features of the signal while eliminating the irrelevant ones. For example, if you want to measure the temperature of an engine, you should use a low-pass filter that can remove the high-frequency noise from the sensor output.

5 Digitize the signal

The fifth step to improve the SNR of automotive sensors is to digitize the signal before transmitting it. Digitization is a technique that converts an analog signal into a digital signal, consisting of discrete values or bits. Digitization can reduce the noise and interference that can affect the analog signal during transmission, as well as enable more advanced processing and analysis of the signal. However, digitization can also introduce errors or artifacts, such as quantization noise, aliasing, or jitter, so you should use a high-resolution and high-speed analog-to-digital converter (ADC) that can capture the signal accurately and faithfully.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?