Methodology to Achieve Accurate Non Cooperative Target Identification Using High Resolution Radar and a Synthetic Database

Jurado-Lucena, Antonio; Errasti-Alcala, Borja; Escot-Bocanegra, David; Fernández-Recio, R.; Poyatos-Martínez, David; Sánchez, Ignacio Montiel

doi:10.1007/978-3-642-13022-9_43

Cited by 2 publications

(2 citation statements)

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“…According to that, in this paper identification of HRRPs coming from data of real in-flight targets is carried out by comparison with a database of simulated/synthetic HRRPs. This approach is barely applied in the open literature [ 2 , 28 , 29 ] but it is a very interesting field due to the ease in the database population and the fast evaluation of algorithms. The main drawback found, as noted, is that predictions have a very clean signature while actual HRRPs suffer from noise and other unwanted effects, making the recognition process similar to a real situation where collected profiles could be noisier than those in the database.…”

Section: Methodsmentioning

confidence: 99%

Non-Cooperative Target Recognition by Means of Singular Value Decomposition Applied to Radar High Resolution Range Profiles

López-Rodríguez¹,

Escot-Bocanegra²,

Fernández-Recio

et al. 2014

Sensors

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Radar high resolution range profiles are widely used among the target recognition community for the detection and identification of flying targets. In this paper, singular value decomposition is applied to extract the relevant information and to model each aircraft as a subspace. The identification algorithm is based on angle between subspaces and takes place in a transformed domain. In order to have a wide database of radar signatures and evaluate the performance, simulated range profiles are used as the recognition database while the test samples comprise data of actual range profiles collected in a measurement campaign. Thanks to the modeling of aircraft as subspaces only the valuable information of each target is used in the recognition process. Thus, one of the main advantages of using singular value decomposition, is that it helps to overcome the notable dissimilarities found in the shape and signal-to-noise ratio between actual and simulated profiles due to their difference in nature. Despite these differences, the recognition rates obtained with the algorithm are quite promising.

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Section: Methodsmentioning

confidence: 99%

Non-Cooperative Target Recognition by Means of Singular Value Decomposition Applied to Radar High Resolution Range Profiles

López-Rodríguez¹,

Escot-Bocanegra²,

Fernández-Recio

et al. 2014

Sensors

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“…Section 3 presents the methodology used in this study for ISAR image generation from actual flying aircrafts data and its recognition, based on the previous work by [6]. The methodology presented requires complex computations implying a high computational burden as it is explained in Section 4.…”

Section: Introductionmentioning

confidence: 99%

Computational Burden Resulting from Image Recognition of High Resolution Radar Sensors

López-Rodríguez

Fernández-Recio

Bravo

et al. 2013

Sensors

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This paper presents a methodology for high resolution radar image generation and automatic target recognition emphasizing the computational cost involved in the process. In order to obtain focused inverse synthetic aperture radar (ISAR) images certain signal processing algorithms must be applied to the information sensed by the radar. From actual data collected by radar the stages and algorithms needed to obtain ISAR images are revised, including high resolution range profile generation, motion compensation and ISAR formation. Target recognition is achieved by comparing the generated set of actual ISAR images with a database of ISAR images generated by electromagnetic software. High resolution radar image generation and target recognition processes are burdensome and time consuming, so to determine the most suitable implementation platform the analysis of the computational complexity is of great interest. To this end and since target identification must be completed in real time, computational burden of both processes the generation and comparison with a database is explained separately. Conclusions are drawn about implementation platforms and calculation efficiency in order to reduce time consumption in a possible future implementation.

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Methodology to Achieve Accurate Non Cooperative Target Identification Using High Resolution Radar and a Synthetic Database

Cited by 2 publications

References 10 publications

Non-Cooperative Target Recognition by Means of Singular Value Decomposition Applied to Radar High Resolution Range Profiles

Non-Cooperative Target Recognition by Means of Singular Value Decomposition Applied to Radar High Resolution Range Profiles

Computational Burden Resulting from Image Recognition of High Resolution Radar Sensors

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