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Journal ArticleDOI

Precession missile feature extraction using sparse component analysis of radar measurements

09 Feb 2012-EURASIP Journal on Advances in Signal Processing (Springer International Publishing)-Vol. 2012, Iss: 1, pp 24

TL;DR: The radar signal model of the precessing conical missile during flight is analyzed and the sparse dictionary which is parameterized by the unknown precession frequency is developed, which establishes the sparse signal model.

AbstractAccording to the working mode of the ballistic missile warning radar (BMWR), the radar return from the BMWR is usually sparse. To recognize and identify the warhead, it is necessary to extract the precession frequency and the locations of the scattering centers of the missile. This article first analyzes the radar signal model of the precessing conical missile during flight and develops the sparse dictionary which is parameterized by the unknown precession frequency. Based on the sparse dictionary, the sparse signal model is then established. A nonlinear least square estimation is first applied to roughly extract the precession frequency in the sparse dictionary. Based on the time segmented radar signal, a sparse component analysis method using the orthogonal matching pursuit algorithm is then proposed to jointly estimate the precession frequency and the scattering centers of the missile. Simulation results illustrate the validity of the proposed method.

Topics: Continuous-wave radar (62%), Radar (59%), Missile (55%), Ballistic missile (54%), Larmor precession (52%)

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Citations
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Journal ArticleDOI
TL;DR: The reconstruction of moving targets' HRRP through CS-based matched filtering algorithms shows that the sub-Nyquist sampled jamming signals, formed by the under-sampled radar signals in scatter-wave jamming configuration, provide a capability of deception jamming.
Abstract: As recently demonstrated, compressive sensing (CS) is potential in exact recovery of an unknown sparse signal from very limited samples. In this paper, sub-Nyquist sampling jamming against inverse synthetic aperture radar (ISAR) imaging is presented, where the CS-based algorithm is applied to the high-resolution range profile (HRRP) reconstruction other than the Doppler profile reconstruction. The reconstruction of moving targets’ HRRP through CS-based matched filtering algorithms shows that the sub-Nyquist sampled jamming signals, formed by the under-sampled radar signals in scatter-wave jamming configuration, provide a capability of deception jamming. The finally reconstructed ISAR images show that the deceptive false-target images retaining the real target information will be induced. Hence, the rational utilization of sub-Nyquist sampling jamming can generate vivid decoys in ISAR countermeasures. Experimental results of the scattering model of the Yak-42 plane are used to verify the correctness of the jamming idea.

22 citations


Cites background from "Precession missile feature extracti..."

  • ...Since the CS-based ISAR imaging has exhibited excellent quality in military application, such as aircraft/ship imaging and feature extraction [9], [10] of non-cooperative targets with less signal acquisition and finer resolution, countermeasures that can generate deceptive false-target images are in high demand in electronic warfare [11]–[15]....

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Journal ArticleDOI
Abstract: Micro-Doppler (MD) caused by the motion of the ballistic missile can contribute to successful recognition of the ballistic missile. Considering the real observation scenario. This paper proposes a method to derive the MD image of the ballistic missile by applying the range-Doppler algorithm (RDA) based on the real ∞ight scenario and analyzes the factor for the real-time MD imaging. Simulation results using the ∞ight trajectory constructed using the real target parameter demonstrate that we need a new cost function for phase adjustment and a new method for range alignment. In addition, matched-flltering needs to be performed in the baseband, and a su-cient PRF is required to prevent discontinuity of the MD image. Dechirping of MD and flltering of the random movement are also needed for a clear MD image. Among the various weapons used in the modern battlefleld, the ballistic missile in∞icts the biggest threat due to its high maneuvering speed and low radar cross section (RCS), and thus defending against the ballistic missile is a major issue. Recently, a theory has been developed to explain micro-Doppler (MD) efiect caused by the micro motion of the target and applied for radar target recognition purpose (1,2). In the case of the ballistic missile, three motion components | spinning, conning and nutation | cause MD, and they can be utilized for target recognition in combination with the motion parameter (1,3,4). However, very little research has been reported on its application to the real ∞ight scenario and the factor that needs to be considered for the real-time MD imaging. In this paper, considering the real observation scenario by a radar, we propose a method to extract an MD signature of a ballistic missile engaged in the real ∞ight scenario by applying the range-Doppler algorithm (RDA), which is generally used to form the inverse synthetic aperture radar (ISAR) image (5{8), and analyze various factors for the real-time high quality MD image. For this purpose, we constructed the ∞ight trajectory by using the real motion parameters of a 500km range scud missile conducted a translation motion compensation (TMC). Then, the time-varying MD image was formed by applying the time-frequency transform (TFT). Various simulations were performed by using the obtained MD image to study the requirement for the real-time MD imaging. Simulation results obtained by using a target composed of the point scatter demonstrate that the MD signature can be successfully constructed by using the range-Doppler algorithm. However, a new method for TMC is required for real-time high-quality MD imaging. In addition, matched-flltering (MF) in the baseband is required to form a focused image, and a su-cient PRF is needed to remove discontinuity. The re∞ected signal needs to be dechirped to reduce the required PRF, and a fllter needs to be designed to remove the random movement.

13 citations


Journal ArticleDOI
Abstract: The micromotion dynamics and geometrical shape are considered to be essential characteristics for exoatmospheric targets discrimination. Many methods have been investigated to retrieve the micromotion features using radar signals returned from targets of a given shape. We explore a way of jointly estimating micromotion dynamics and geometrical shape parameters from the infrared (IR) signals of targets in remote detection distance. It is found that the micromotion dynamics of the target would induce a periodic fluctuating variation on the IR irradiance intensity signature. In addition to the micromotion characteristics, the fluctuation could also reflect target structure properties, which offer a possible clue in extracting the features of micromotion dynamics and geometrical shape. Thus, the data model of target IR irradiance intensity signatures induced by micromotion patterns including spinning, coning, and tumbling is developed, and a method of parameters estimation based on joint optimization analysis techniques is proposed. Experimental results demonstrated that the parameters of target micromotion dynamics and geometrical shape can be effectively estimated using the proposed method, if the input signature contains multiple dominant frequency components.

13 citations


Journal ArticleDOI
TL;DR: A new approach, named sinusoidal frequency modulation sparse recovery (SFMSR) for m-D analysis with LFLRR, by exploiting the micro motion spectrum sparsity in SFM signal space and employing the Fourier modulation dictionary.
Abstract: Low-frequency long-range radars (LFLRRs) are assumed to lack the ability of extracting targets micro motion signature, due to their low and nonuniform track update rate, as well as the weak micro Doppler (m-D) owing to their large wave length. The recently proposed sinusoidal frequency modulated (SFM) Fourier transform can achieve a longer integral period gain, and consequently provides a new perspective for extracting weak m-D signature. However, its direct application is unavailable for LFLRRs, since their track update rate is very low and may not even be constant. This paper derives a new approach, named sinusoidal frequency modulation sparse recovery (SFMSR) for m-D analysis with LFLRR, by exploiting the micro motion spectrum sparsity in SFM signal space. SFMSR employs the Fourier modulation dictionary, which is determined only by the frequency in SFM signal space. Unlike other sparse representation-based methods whose dictionary is discretization of a 3-D space parameterized by the micro motion amplitude, frequency, and initial phase, the SFMSR reduces the m-D analysis to 1-D parameter optimization, and therefore can enhance the precision, stability, and computational efficiency simultaneously. The temporally correlated sparse Bayesian learning in SFM signal space is employed to decompose the signal and produce highly sparse solutions. The simulation results indicate that the proposed method outperforms the existing methods in accuracy and robustness, which can provide satisfactory performance even when the carrier frequency is 430 MHz and the average data rate is 0.5 Hz.

6 citations


Cites methods from "Precession missile feature extracti..."

  • ...Recent developing area of sparse representation (SR) brought out several SR based m-D analysis algorithms, such as orthogonal matching pursuit (OMP) based [22], [23] and Sparse Bayesian Learning (SBL) based methods [24]....

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Proceedings ArticleDOI
06 Jul 2013
TL;DR: Considering the rotationally symmetric targets, the sparse representation model of the ballistic midcourse targets with micro-motion is established and the sparse recovery algorithm named SBL (Sparse Bayesian Learning) is analyzed, which can provide a much sparser solution than the general sparse recovery algorithms.
Abstract: The ISAR (inverse synthetic aperture radar) imaging technology is an important tool for the ballistic missile midcourse target recognitions. Considering the rotationally symmetric targets, the sparse representation model of the ballistic midcourse targets with micro-motion is established. The sparse recovery algorithm named SBL (Sparse Bayesian Learning) is analyzed, which can provide a much sparser solution than the general sparse recovery algorithms. Based on the newly developed CS (Compress sensing) theory, the ISAR imaging of the ballistic missile is reconstructed by using only a few echoes. Simulation results verify the validity and superiority of the proposed method.

5 citations


Cites methods from "Precession missile feature extracti..."

  • ...A sparse representation method based on orthogonal matching pursuit algorithm (OMP) algorithm is proposed to jointly estimate the precession frequency and the scattering centers of the missile in [10]....

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