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Estimating motion parameters of the maneuvering target is a difficult thing currently for most of airborne synthetic aperture radar (SAR) due to the complex motion, which usually results into a defocus-blurred SAR image of the target. To avoid the difficulty, this paper proposes a high-resolution imaging method via airborne multiple-input and multiple-output (MIMO) radar based on a hybrid sampling procedure, where the single snapshot of MIMO radar and the synthetic aperture of SAR are combined. Different from the classical SAR, the novel method only compensates the movement by the geographic information between the target and the airborne radar, not need of the Doppler information. Therefore, the difficulty associated with the Doppler estimation in SAR imaging procedure can effectively be avoided. Simulation results prove the availability of the proposed algorithm for the maneuvering target imaging. [ABSTRACT FROM PUBLISHER]

In this paper, we consider the challenging problem of tracking a maneuvering target with abrupt accelerations and introduce a new model based on GARCH process. We formulate the acceleration of dynamic model by stochastic differential equation (SDE) with adaptive coefficients and stochastic volatility. Our adaptive state space approach provides a novel dynamic model that naturally facilitates the physical constraints from the target acceleration jumps to the high maneuvering dynamics model in a probabilistic form, thereby achieving improved tracking accuracy and efficiency compared to competing techniques. Finally, the effectiveness and capabilities of our proposed strategy are demonstrated and validated through a simulation study. [ABSTRACT FROM PUBLISHER]

A new three-dimensional guidance law with high impact angle constraints used for striking ground moving targets is designed based on back-stepping control approach. The kinematics between the missile and the target are established in line-of-sight (LOS) frame. To ensure the required impact angle and small miss distance, two step controllers are designed based on Lyapunov method. The first step controller guarantees the LOS angle in vertical plane to converge to the desired angle. The second step controller can stabilize the overall system while maintaining minimum LOS rate, and thus the smallest miss distance can be achieved indirectly. Simulation results illustrate the efficiency. [ABSTRACT FROM PUBLISHER]

This paper presents a novel single target particle filter with spawn model and particle labeling approach, abbreviated SL-PF. The purpose of this filter is to detect instantaneously occurring target maneuvers, e.g. course changes of maritime targets, and to provide accurate tracking performance before and after the maneuvers. The key idea is to borrow the spawn model from the probability hypothesis density (PHD) filter since this model is naturally suited for these kinds of maneuvers. Secondly, each particle in the filter carries a label which is updated in a systematic manner in the spawning step so that it is possible to recognize spawned particles representing a target maneuver. This provides an integrated maneuver detection procedure within the particle filter. Monte Carlo simulations verify the SL-PF approach and indicate a significant estimation accuracy improvement compared to a conventional particle filter. [ABSTRACT FROM PUBLISHER]

Based on compressive sensing theory, a new method for high resolution inverse aperture radar (ISAR) imaging of maneuvering target is proposed. In this method, only a few measurements in ambiguity function plane are sampled to reconstruct the time-frequency distribution by solving the inverse problem using basis pursuit method. With a Gaussian window as a sampling function, the trade-off between the cross-term suppression and resolution is properly dealt with, and the proposed method obtains clear ISAR image of maneuvering target with a high resolution. The effectiveness of the proposed method is studied with testing data. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a new model to track a maneuvering target with abrupt accelerations. We utilize the stochastic differential equation (SDE) to model acceleration of a maneuvering target with GARCH process as the model for the SDE volatility. The proposed tracking algorithm operates in both the non-manoeuvring and the manoeuvring modes and the manoeuvre detection procedure is eliminated. In the proposed scheme, the original state and stochastic volatility are estimated simultaneously with a particle filter. We show analytically that target tracking performance by considering GARCH acceleration model is improved. Finally, the effectiveness and capabilities of our proposed strategy are demonstrated and validated through a simulation study. [ABSTRACT FROM PUBLISHER]