The so-called Multi-sensor Information Fusion (MSIF) is the use of computer technology to automatically analyze and synthesize information and data from multiple sensors or multiple sources under certain criteria to complete the required decisions and estimates. The information processing process.
Multi-sensor information fusion is an information processing technique for containing multiple or multiple sensors at different locations. With the development of sensor application technology, data processing technology, computer software and hardware technology and industrialization control technology, multi-sensor information fusion technology has formed a hot emerging discipline and technology.
The basic principle of multi-sensor information fusion technology is just like the process of the human brain's comprehensive processing of information. Multi-level and multi-space information is complemented and optimized by various sensors, resulting in a consistent interpretation of the observation environment. In this process, it is necessary to make full use of multi-source data for reasonable dominance and use. The ultimate goal of information fusion is to obtain more useful information based on multiple levels and combinations of information based on the separation observation information obtained by each sensor. This not only utilizes the advantages of multiple sensors working in tandem with each other, but also comprehensively processes data from other sources to improve the intelligence of the entire sensor system. The multi-sensor fusion system has four notable features:
1. Redundancy of information: For a certain feature of the environment, multiple pieces of information can be obtained by multiple sensors (or multiple different times of a single sensor). The information is redundant and has different reliability. With fusion processing, more accurate and reliable information can be extracted from it. In addition, the redundancy of information can improve the stability of the system, so as to avoid the impact on the entire system caused by the failure of a single sensor.
2. Complementarity of information: Different kinds of sensors can provide different kinds of information for the system. The objects described by these information are different environmental characteristics and they are mutually complementary. If you define a coordinate space that consists of all features, then the information provided by each sensor only belongs to a subspace of the entire space, and is independent of the space formed by other sensors.
3, the timeliness of information processing: the processing of each sensor independent of each other, the entire process can use parallel thermal processing mechanisms, so that the system has a faster processing speed, provide more timely processing results.
4, the low cost of information processing: multiple sensors can be used to obtain the equivalent amount of information can be obtained by a single sensor. On the other hand, if the information provided by a single sensor is not used to implement other functions, the sum of the cost of a single sensor and the cost of multiple sensors is comparable.
Information fusion, as an integrated process for multi-sensor information, is inherently complex. In the process of information fusion processing, according to the difference of the original data processing methods, the information fusion system has three main architectures: centralized, distributed, and hybrid.
1. Centralized: The centralized type sends the raw data obtained by each sensor directly to the central processor for fusion processing, which can realize real-time convergence. The data processing has high precision and the algorithm is flexible. The disadvantages are high requirements on the processor and reliability. Low, large amount of data, it is difficult to achieve.
2. Distributed: Each sensor collects the raw data obtained locally, including the preprocessing, classification, and extraction of feature information of the original data. Each decision is made through their own decision criteria, and the results are sent to the fusion center. Fusion to get the final decision. Distributed communication bandwidth has low requirements, fast calculation speed, good reliability and continuity, but tracking accuracy is not centralized and high.
3. Hybrid: In most cases, the two are combined differently to form a hybrid structure. It retains the advantages of the above two types of systems, but it has to pay a relatively high price for communications and computing. However, such systems also have the advantage that these two types of systems are incomparable, and they are often used in practical situations.
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