Infrared false target is an important mean to induce the infrared-guided weapons,and the key issue is how to keep the surface temperature of the infrared false target to be the same as that of the object to be protect...Infrared false target is an important mean to induce the infrared-guided weapons,and the key issue is how to keep the surface temperature of the infrared false target to be the same as that of the object to be protected.One-dimensional heat transfer models of a metal plate and imitative material were established to explore the influences of the thermophysical properties of imitative material on the surface temperature difference（STD） between the metal plate and imitative material which were subjected to periodical ambient conditions.It is elucidated that the STD is determined by the imitative material’s dimensionless thickness（dim*,） and the thermal inertia(Pim).When dim* is above 1.0,the STD is invariable as long as Pim is a constant.And if the dimensionless thickness of metal plate（d,m*） is also larger than 1.0,the STD approaches to zero as long as Pimis the same as the thermal inertia of metal plate（Pm）.When dim* is between 0.08 and 1,the STD varies irregularly with Pim and dim*.However,if dm* is also in the range of 0.08-1,the STD approaches to zero on condition that Pim=Pm and dim*= dm*.If dim*,is below 0.08,the STD is unchanged when Pimdim* is a constant.And if dm* is also less than 0.08,the STD approaches to zero as long as Pimdim* = Pmdm*.Furthermore,an applicationoriented discussion indicates that the imitative material can be both light and thin via the application of the phase change material with a preset STD because of its high specific heat capacity during the phase transition process.展开更多
A new constant false alarm rate （CFAR） target detector for synthetic aperture radar （SAR） images is developed. For each pixel under test, both the local probability density function （PDF） of the pixel and the cl...A new constant false alarm rate （CFAR） target detector for synthetic aperture radar （SAR） images is developed. For each pixel under test, both the local probability density function （PDF） of the pixel and the clutter PDF in the reference window are estimated by the non-parametric density estimation. The target detector is defined as the mean square error （MSE） distance between the two PDFs. The CFAR detection in SAR images having multiplicative noise is achieved by adaptive kernel bandwidth proportional to the clutter level. In addition, for obtaining a threshold with respect to a given probability of false alarm （PFA）, an unsupervised null distribution fitting method with outlier rejection is proposed. The effectiveness of the proposed target detector is demonstrated by the experiment result using the RADATSAT-2 SAR image.展开更多
Ship detection using synthetic aperture radar(SAR)plays an important role in marine applications.The existing methods are capable of quickly obtaining many candidate targets,but numerous non-ship objects may be wrongl...Ship detection using synthetic aperture radar(SAR)plays an important role in marine applications.The existing methods are capable of quickly obtaining many candidate targets,but numerous non-ship objects may be wrongly detected in complex backgrounds.These non-ship false alarms can be excluded by training discriminators,and the desired accuracy is obtained with enough verified samples.However,the reliable verification of targets in large-scene SAR images still inevitably requires manual interpretation,which is difficult and time consuming.To address this issue,a semisupervised heterogeneous ensemble ship target discrimination method based on a tri-training scheme is proposed to take advantage of the plentiful candidate targets.Specifically,various features commonly used in SAR image target discrimination are extracted,and several acknowledged classification models and their classic variants are investigated.Multiple discriminators are constructed by dividing these features into different groups and pairing them with each model.Then,the performance of all the discriminators is tested,and better discriminators are selected for implementing the semisupervised training process.These strategies enhance the diversity and reliability of the discriminators,and their heterogeneous ensemble makes more correct judgments on candidate targets,which facilitates further positive training.Experimental results demonstrate that the proposed method outperforms traditional tritraining.展开更多
Collaboration in wireless sensor systems must be fault-tolerant due to the harsh environmental conditions at which such systems can be deployed. This paper focuses on finding the signal processing algorithms for colla...Collaboration in wireless sensor systems must be fault-tolerant due to the harsh environmental conditions at which such systems can be deployed. This paper focuses on finding the signal processing algorithms for collaborative target detection based on the generalized approach to signal processing （GASP） in the presence of noise. The signal processing algorithms are efficient in terms of communication cost, precision, accuracy, and number of faulty sensors tolerable in the wireless sensor systems. Two types of generalized signal processing algorithms, namely, value fusion and decision fusion constructed according to GASP in the presence of noise, are identified first. When comparing their performance and communication overhead, the decision fusion algorithm is found to become superior to the value fusion algorithm as the ratio of faulty sensors to fault free sensors increases. The use of GASP under designing the value and decision fusion algorithms in wireless sensor systems allows us to obtain the same performance, but at low values of signal energy, as well as under employment of the universally adopted signal processing algorithms widely used in practice.展开更多
基金funded by the National Natural Science Foundation of China (No. 51576188)
文摘Infrared false target is an important mean to induce the infrared-guided weapons,and the key issue is how to keep the surface temperature of the infrared false target to be the same as that of the object to be protected.One-dimensional heat transfer models of a metal plate and imitative material were established to explore the influences of the thermophysical properties of imitative material on the surface temperature difference（STD） between the metal plate and imitative material which were subjected to periodical ambient conditions.It is elucidated that the STD is determined by the imitative material’s dimensionless thickness（dim*,） and the thermal inertia(Pim).When dim* is above 1.0,the STD is invariable as long as Pim is a constant.And if the dimensionless thickness of metal plate（d,m*） is also larger than 1.0,the STD approaches to zero as long as Pimis the same as the thermal inertia of metal plate（Pm）.When dim* is between 0.08 and 1,the STD varies irregularly with Pim and dim*.However,if dm* is also in the range of 0.08-1,the STD approaches to zero on condition that Pim=Pm and dim*= dm*.If dim*,is below 0.08,the STD is unchanged when Pimdim* is a constant.And if dm* is also less than 0.08,the STD approaches to zero as long as Pimdim* = Pmdm*.Furthermore,an applicationoriented discussion indicates that the imitative material can be both light and thin via the application of the phase change material with a preset STD because of its high specific heat capacity during the phase transition process.
基金supported by the National Natural Science Foundation of China (40871157 41171317)the Foundation of Advance Research of Science and Technology for Chinese National Defence(9140C620201902)
文摘A new constant false alarm rate （CFAR） target detector for synthetic aperture radar （SAR） images is developed. For each pixel under test, both the local probability density function （PDF） of the pixel and the clutter PDF in the reference window are estimated by the non-parametric density estimation. The target detector is defined as the mean square error （MSE） distance between the two PDFs. The CFAR detection in SAR images having multiplicative noise is achieved by adaptive kernel bandwidth proportional to the clutter level. In addition, for obtaining a threshold with respect to a given probability of false alarm （PFA）, an unsupervised null distribution fitting method with outlier rejection is proposed. The effectiveness of the proposed target detector is demonstrated by the experiment result using the RADATSAT-2 SAR image.
基金The National Natural Science Foundation of China under contract No.61971455.
文摘Ship detection using synthetic aperture radar(SAR)plays an important role in marine applications.The existing methods are capable of quickly obtaining many candidate targets,but numerous non-ship objects may be wrongly detected in complex backgrounds.These non-ship false alarms can be excluded by training discriminators,and the desired accuracy is obtained with enough verified samples.However,the reliable verification of targets in large-scene SAR images still inevitably requires manual interpretation,which is difficult and time consuming.To address this issue,a semisupervised heterogeneous ensemble ship target discrimination method based on a tri-training scheme is proposed to take advantage of the plentiful candidate targets.Specifically,various features commonly used in SAR image target discrimination are extracted,and several acknowledged classification models and their classic variants are investigated.Multiple discriminators are constructed by dividing these features into different groups and pairing them with each model.Then,the performance of all the discriminators is tested,and better discriminators are selected for implementing the semisupervised training process.These strategies enhance the diversity and reliability of the discriminators,and their heterogeneous ensemble makes more correct judgments on candidate targets,which facilitates further positive training.Experimental results demonstrate that the proposed method outperforms traditional tritraining.
文摘Collaboration in wireless sensor systems must be fault-tolerant due to the harsh environmental conditions at which such systems can be deployed. This paper focuses on finding the signal processing algorithms for collaborative target detection based on the generalized approach to signal processing （GASP） in the presence of noise. The signal processing algorithms are efficient in terms of communication cost, precision, accuracy, and number of faulty sensors tolerable in the wireless sensor systems. Two types of generalized signal processing algorithms, namely, value fusion and decision fusion constructed according to GASP in the presence of noise, are identified first. When comparing their performance and communication overhead, the decision fusion algorithm is found to become superior to the value fusion algorithm as the ratio of faulty sensors to fault free sensors increases. The use of GASP under designing the value and decision fusion algorithms in wireless sensor systems allows us to obtain the same performance, but at low values of signal energy, as well as under employment of the universally adopted signal processing algorithms widely used in practice.
