Target Classification With Low-Resolution Surveillance Radars Based on Multifractal Features

Abstract

Abstract-The multifractal characteristics of return signals from aircraft targets in conventional radars offer a fine description of dynamic characteristics which induce the targets' echo structure; therefore they can provide a new way for aircraft target classification and recognition with low-resolution surveillance radars. On basis of introducing the mathematical model of return signals from aircraft targets in conventional radars, the paper analyzes the multifractal characteristics of the return signals as well as the extraction method of their multifractal features by means of the multifractal analysis of measures, and puts forward a multifractal-feature-based classification method for three types of aircraft targets (including jet aircrafts, propeller aircrafts and helicopters) from the viewpoint of pattern classification. The analysis shows that the conventional radar return signals from the three types of aircraft targets have significantly different multifractal characteristics, and the defined characteristic parameters can be used as effective features for aircraft target classification and recognition. The results of classification experiments validate the proposed method.

Research on Analysis of Multifractal Correlation Characteristics of Aircraft Echoes and Classification of Targets in Surveillance Radars

“…Here the aforementioned real-recorded echo data from six types of aircraft targets will be adopted as the experimental data to do the classification experiments, and the classification method based on multifractal features (CMMF) proposed in [13] will be taken as the contrast to analyze the performance of the classification method based on multifractal correlation features (CMMCF).…”

“…Yet it is difficult to fully characterize the complex nature of an aircraft echo by using only a single fractal dimension. Therefore, [12][13][14] perform multifractal modeling, characteristic analysis, and feature extraction on simulated and real-recorded aircraft echo data from low-resolution radars by means of the multifractal analysis of measures, and put forward some classification methods based on multifractal features. In spite of this, multifractal theory only performs statistical analysis on the singularity index of an arbitrary point in geometry subsets of a fractal object, and then determines the multifractal spectrum, while the measure on the fractal object is generated by a potential series process.…”

Effect of Threshold Value on the Performance of Natural Frequency-Based Radar Target Recognition

“…The reflected signal of the radar target can be simulated using scattering analysis of the radar target [60][61][62][63][64][65][66][67][68][69]. In addition to radar detection and tracking, there have been many studies on radar target recognition [70][71][72][73][74][75][76][77][78][79][80][159][160][161][162][163][164][165][166].…”

“…There are many radar signatures which can be used for radar target recognition: Natural frequencies of radar target [159][160][161][162][163][164][165][166], high resolution range (HRR) profiles [72,[75][76][77][78][79][80] of radar target, microwave image of the radar target [1,26,31,50,55,70,73,[81][82][83][84][85][86][87][88][89][90][91][92][93][94][95][96][97][98][99][100], and inverse synthetic aperture radar (ISAR) [55, 86-100, 125, 126] image proved to be useful features for target recognition. Jet engine modulation and helicopter modulation [127,128] have also been known as useful features for target recognition.…”

Classification of Aircraft Targets With Surveillance Radars Based on Fuzzy Fractal Features

“…Different types of aircraft targets often have different structure and rotating parts and different nonrigid vibration and JEM modulation characteristics. If these nonlinear modulation features which reflect the physical characteristics of an aircraft target can be extracted, then one may apply them to aircraft target classification and recognition directly [19][20][21]. Therefore, the paper plans to adopt the nonlinear research method -fuzzy fractal theory to analyze the characteristics of conventional radar return signals from aircraft targets, and on this basis puts forward a fuzzyfractal-feature-based classification method so as to identify different types of aircraft targets in condition of no compensation for airframe echo components.…”