Abstract
With the development of the shipping industry, Automatic Identification System (AIS) used for ship communication becomes more and more important. Aiming at the problem of mixing position estimation of AIS mixed signals, this paper improves the double sliding-window detection algorithm to estimate the mixing position of miscellaneous signals accurately. There is a significant difference in energy between the aliased and unmixed parts of the mixed signal. When unmixed parts just enter one of the energy detections windows, the decision function reaches its peak value by establishing a proper decision function, that is to say, the position of the beginning and end of the mixing part is estimated. The simulation results show that the proposed algorithm which is compared with the frequency and amplitude detection algorithm can achieve the mixing position estimation with low complexity and strong robustness, and the estimation accuracy is close to the Cramer-Rao Bound under the condition of the high signal-to-noise ratio.
Highlights
Ship Automatic Identification System (AIS) that consists of shore-based facilities and ship-borne equipment is another type of digital navigation aid system and equipment
When the unaligned part of the signal completely enters the amplified energy detection window, the decision function just reaches the peak value; and at other times, the magnitude of the decision result is reduced by multiplying the energy difference in the adjacent window
The closer the energy of the adjacent window is to the effect on the magnitude of the final decision function, the more significant the effect is when the decision function reaches its peak value
Summary
Ship Automatic Identification System (AIS) that consists of shore-based facilities and ship-borne equipment is another type of digital navigation aid system and equipment. In order to accurately estimate the starting and ending positions of mixing signals, this paper improves the traditional double-sliding window detection algorithm, splits the traditional double-sliding window into four energy detection windows, and modifies the decision function. The improved algorithm only involves the energy ratio of signals, which can accurately estimate the mixing position of mixed signals under low complexity, and maintain the excellent performance of the traditional double-sliding window detection algorithm. The improved algorithm eliminates the influence of signal delay, phase and other factors It can accurately detect the starting and ending position of the mixing part of the mixed signal under the condition of great cost savings, which has a strong practicability
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