In order to solve the problem that the global navigation satellite system（GNSS） receivers can hardly detect the GNSS spoofing when they are deceived by a spoofer,a model-based approach for the identification of the ...In order to solve the problem that the global navigation satellite system（GNSS） receivers can hardly detect the GNSS spoofing when they are deceived by a spoofer,a model-based approach for the identification of the GNSS spoofing is proposed.First,a Hammerstein model is applied to model the spoofer/GNSS transmitter and the wireless channel.Then,a novel method based on the uncultivated wolf pack algorithm（UWPA） is proposed to estimate the model parameters.Taking the estimated model parameters as a feature vector,the identification of the spoofing is realized by comparing the Euclidean distance between the feature vectors.Simulations verify the effectiveness and the robustness of the proposed method.The results show that,compared with the other identification algorithms,such as least square（LS）,the iterative method and the bat-inspired algorithm（BA）,although the UWPA has a little more time-eomplexity than the LS and the BA algorithm,it has better estimation precision of the model parameters and higher identification rate of the GNSS spoofing,even for relative low signal-to-noise ratios.展开更多
Deception is widespread throughout the animal kingdom and various deceptive strategies are exemplified by social parasites. These are species of ants, bees and wasps that have evolved to invade, survive and reproduce ...Deception is widespread throughout the animal kingdom and various deceptive strategies are exemplified by social parasites. These are species of ants, bees and wasps that have evolved to invade, survive and reproduce within a host colony of another social species. This is achieved principally by chemical deception that tricks the host workers into treating the invading parasite as their own kin. Achieving levels of acceptance into typically hostile host colonies requires an amazing level of decep- tion as social insects have evolved complex species- and colony-specific recognition systems. This allows the detection of for- eigners, both hetero- and con-specific. Therefore, social parasitic ants not only have to overcome the unique species recognition profiles that each ant species produces, but also the subtle variations in theses profiles which generate the colony-specific profiles We present data on the level of chemical similarity between social parasites and their hosts in four different systems and then discuss these data in the wider context with previous studies, especially in respect to using multivariate statistical methods when looking for differences in these systems.展开更多
基金The National Natural Science Foundation of China(No.61271214,61471152)the Postdoctoral Science Foundation of Jiangsu Province(No.1402023C)the Natural Science Foundation of Zhejiang Province(No.LZ14F010003)
文摘In order to solve the problem that the global navigation satellite system（GNSS） receivers can hardly detect the GNSS spoofing when they are deceived by a spoofer,a model-based approach for the identification of the GNSS spoofing is proposed.First,a Hammerstein model is applied to model the spoofer/GNSS transmitter and the wireless channel.Then,a novel method based on the uncultivated wolf pack algorithm（UWPA） is proposed to estimate the model parameters.Taking the estimated model parameters as a feature vector,the identification of the spoofing is realized by comparing the Euclidean distance between the feature vectors.Simulations verify the effectiveness and the robustness of the proposed method.The results show that,compared with the other identification algorithms,such as least square（LS）,the iterative method and the bat-inspired algorithm（BA）,although the UWPA has a little more time-eomplexity than the LS and the BA algorithm,it has better estimation precision of the model parameters and higher identification rate of the GNSS spoofing,even for relative low signal-to-noise ratios.
文摘Deception is widespread throughout the animal kingdom and various deceptive strategies are exemplified by social parasites. These are species of ants, bees and wasps that have evolved to invade, survive and reproduce within a host colony of another social species. This is achieved principally by chemical deception that tricks the host workers into treating the invading parasite as their own kin. Achieving levels of acceptance into typically hostile host colonies requires an amazing level of decep- tion as social insects have evolved complex species- and colony-specific recognition systems. This allows the detection of for- eigners, both hetero- and con-specific. Therefore, social parasitic ants not only have to overcome the unique species recognition profiles that each ant species produces, but also the subtle variations in theses profiles which generate the colony-specific profiles We present data on the level of chemical similarity between social parasites and their hosts in four different systems and then discuss these data in the wider context with previous studies, especially in respect to using multivariate statistical methods when looking for differences in these systems.
