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Article summary:
1. This paper reviews different random error signal processing models that have been developed for MEMS inertial sensor precision improvement.
2. Forty-nine representative papers were downloaded and carefully reviewed, from which 30 mainstream algorithms were extracted and categorized into seven groups.
3. The development trend of MEMS inertial sensor technology and its application prospects were presented.
Article analysis:
The article is generally reliable and trustworthy, as it provides a comprehensive overview of the current state of research on random error reduction algorithms for MEMS inertial sensor accuracy improvement. The authors conducted an in-depth literature search on several databases, including Web of Science, IEEE Xplore, Science Direct, and Association for Computing Machinery Digital Library, to identify relevant studies published in journal or conference formats within the last 10 years. Furthermore, the authors provided a summary of the models developed in the studies along with their working principles, application domain, and conclusions made in the studies.
However, there are some potential biases that should be noted when reading this article. Firstly, the authors did not provide any evidence to support their claims about the advantages of MEMS inertial sensors such as small size, low cost, high precision and ease of integration. Secondly, while they discussed various applications of MEMS inertial sensors such as medical devices for health care to defense and military weapons, they did not explore any counterarguments or possible risks associated with these applications. Finally, while they discussed bias stability as an important parameter to reflect accuracy of inertial sensors, they did not present both sides equally by providing evidence for why bias stability is important or how it can be improved.
In conclusion, this article is generally reliable and trustworthy but there are some potential biases that should be noted when reading it.