DOI: 10.38007/978-1-80053-543-5

In today's era of rapid information technology development, various signal sources are constantly emerging and becoming increasingly complex. Traditional signal processing methods are no longer sufficient to meet the demands of practical applications for accuracy and efficiency. High-dimensional signal processing technology has emerged and gradually become an important research direction in the information field. High-dimensional signal processing encompasses several key stages, among which detection, localization, and dynamic tracking are core components that jointly support the efficient operation of numerous fields. From signal recognition in communication systems to target tracking in radar monitoring, and lesion detection in medical imaging, its applications are wide-ranging and crucial. In-depth research into these three stages is of paramount importance for improving the overall performance of signal processing. 

Detection is the first step in high-dimensional signal processing, undertaking the crucial task of accurately identifying target signals from complex high-dimensional signal environments. In real-world scenarios, high-dimensional signals are often accompanied by a large amount of noise and interference. This irrelevant information can severely affect the judgment of target signals. The detection stage employs a series of advanced algorithms and technologies to meticulously analyze and filter the acquired high-dimensional signals, eliminating useless noise and interference, thereby accurately determining the presence of target signals and laying a solid foundation for subsequent localization and dynamic tracking. If the detection stage deviates, it will directly lead to errors in subsequent work, resulting in wasted resources and inaccurate results. Therefore, the reliability and accuracy of the detection stage are prerequisites for the smooth progress of high-dimensional signal processing.  

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