Phased array radar has been applied broadly because of its sound performance.But signal of phased array radar is of a wide variety of types.Therefore,recognition of phased array radar is the most puzzling aspect of th...Phased array radar has been applied broadly because of its sound performance.But signal of phased array radar is of a wide variety of types.Therefore,recognition of phased array radar is the most puzzling aspect of the whole emitter identification domain.To solve the problem,the article proposes the method that identifies phased array radar by pulse amplitude information,and studies the phased array radar,models transmit signal of them,and receiving signal by radar countermeasure reconnaissance receiver.From constructing template of pulse train's amplitude vector of mechanical scanning radar,computing distance of samples and standard template,finding threshold of the template matching arithmetic,the article puts forward the template matching algorithm of radar beam scan type recognition to identify phased array radar automatically.展开更多
This paper represents a template matching using statistical model and parametric template for multi-template. This algorithm consists of two phases: training and matching phases. In the training phase, the statistical...This paper represents a template matching using statistical model and parametric template for multi-template. This algorithm consists of two phases: training and matching phases. In the training phase, the statistical model created by principal component analysis method (PCA) can be used to synthesize multi-template. The advantage of PCA is to reduce the variances of multi-template. In the matching phase, the normalized cross correlation (NCC) is employed to find the candidates in inspection images. The relationship between image block and multi-template is built to use parametric template method. Results show that the proposed method is more efficient than the conventional template matching and parametric template. Furthermore, the proposed method is more robust than conventional template method.展开更多
Cross-correlation （CC） is the most time-consuming in the implementation of image matching algorithms based on the correlation method. Therefore, how to calculate CC fast is crucial to real-time image matching. This ...Cross-correlation （CC） is the most time-consuming in the implementation of image matching algorithms based on the correlation method. Therefore, how to calculate CC fast is crucial to real-time image matching. This work reveals that the single cascading multiply-accumulate （CAMAC） and concurrent multiply-accumulate （COMAC） architectures which have been widely used in the past, actually, do not necessarily bring about a satisfactory time performance for CC. To obtain better time performance and higher resource efficiency, this paper proposes a configurable circuit involving the advantages of CAMAC and COMAC for a large amount of multiply-accumulate （MAC） operations of CC in exhaustive search. The proposed circuit works in an array manner and can better adapt to changing size image matching in real-time processing. Experimental results demonstrate that this novel circuit which involves the two structures can complete vast MAC calculations at a very high speed. Compared with existing related work, it improves the computation density further and is more flexible to use.展开更多
基金Supported by the National Science and Technology Supported Program of China(No.2011BAH24B06)
文摘Phased array radar has been applied broadly because of its sound performance.But signal of phased array radar is of a wide variety of types.Therefore,recognition of phased array radar is the most puzzling aspect of the whole emitter identification domain.To solve the problem,the article proposes the method that identifies phased array radar by pulse amplitude information,and studies the phased array radar,models transmit signal of them,and receiving signal by radar countermeasure reconnaissance receiver.From constructing template of pulse train's amplitude vector of mechanical scanning radar,computing distance of samples and standard template,finding threshold of the template matching arithmetic,the article puts forward the template matching algorithm of radar beam scan type recognition to identify phased array radar automatically.
文摘This paper represents a template matching using statistical model and parametric template for multi-template. This algorithm consists of two phases: training and matching phases. In the training phase, the statistical model created by principal component analysis method (PCA) can be used to synthesize multi-template. The advantage of PCA is to reduce the variances of multi-template. In the matching phase, the normalized cross correlation (NCC) is employed to find the candidates in inspection images. The relationship between image block and multi-template is built to use parametric template method. Results show that the proposed method is more efficient than the conventional template matching and parametric template. Furthermore, the proposed method is more robust than conventional template method.
文摘Cross-correlation （CC） is the most time-consuming in the implementation of image matching algorithms based on the correlation method. Therefore, how to calculate CC fast is crucial to real-time image matching. This work reveals that the single cascading multiply-accumulate （CAMAC） and concurrent multiply-accumulate （COMAC） architectures which have been widely used in the past, actually, do not necessarily bring about a satisfactory time performance for CC. To obtain better time performance and higher resource efficiency, this paper proposes a configurable circuit involving the advantages of CAMAC and COMAC for a large amount of multiply-accumulate （MAC） operations of CC in exhaustive search. The proposed circuit works in an array manner and can better adapt to changing size image matching in real-time processing. Experimental results demonstrate that this novel circuit which involves the two structures can complete vast MAC calculations at a very high speed. Compared with existing related work, it improves the computation density further and is more flexible to use.
