Robust GMTI Scheme for Highly Squinted Hypersonic Vehicle-Borne Multichannel SAR in Dive Mode

While there are recent researches on hypersonic vehicle-borne multichannel synthetic aperture radar in ground moving target indication (HSV-MC-SAR/GMTI), this article, which specifically explores a robust GMTI scheme for the highly squinted HSV-MC-SAR in dive mode, is novel. First, an improved equivalent range model (IERM) for stationary targets and GMTs is explored, which enjoys a concise expression and therefore offers the potential to simplify the GMTI process. Then, based on the proposed model, a robust GMTI scheme is derived in detail, paying particular attention to Doppler ambiguity arising from the high-speed and high-resolution wide-swath. Furthermore, it retrieves the accurate two-dimensional speeds of GMTs and realizes the satisfactory performance of clutter rejection and GMT imaging, generating the matched beamforming and enhancing the GMT energy. Finally, it applies the inverse projection to revise the geometry shift induced by the vertical speed. Simulation examples are used to verify the proposed GMTI scheme.

A Study on the Range Equation Modeling for Multichannel Medium-Earth-Orbit SAR-GMTI Systems

This paper studies the range equation modeling of a ground moving target for multichannel medium-Earth-orbit (MEO) synthetic aperture radar (SAR) ground moving target indication (GMTI), an issue which is challenging to tackle due to the non-linear motion of the radar platform and the Earth rotation. In the paper, the coordinates of the multichannel MEO SAR and the target, as well as the target’s range equation with respect to each channel, are developed. Moreover, an expression of concise form is derived for the target’s quadratic-approximated range equation, which will benefit the design of GMTI methods. Furthermore, theoretical analyses are conducted to reveal the dependency between the accuracy of the quadratic-approximated range equation and the parameters of the radar and the target. Numerical simulations are carried out to investigate the influence of the quadratic approximation of the range equation on the GMTI performance and to figure out the quadratic-approximated range equation’s scope of application.

An Interrupted Sampling Scattered Wave Deception Jamming Method against Three-Channel SAR GMTI

An important problem is how to generate false moving targets, whose relocated azimuth position is similar to that of real moving targets. To solve this problem, an interrupted sampling scattered wave deception jamming method against three-channel synthetic aperture radar ground moving target indication (SAR GMTI) is proposed. A stationary jammer uses a controllable jammer antenna to generate verisimilar moving targets by controlling velocity and initial position of jammer beam footprint. The antenna sampled moves along the different tracks. For each track, the slant history of jamming signal is changed varying with different pulse recurrence intervals (PRI), and the movement of the footprint will introduce a Doppler frequency in jamming the signal. By analyzing parameters’ difference between echoes and jamming signal, the velocity and the initial position of the footprint will be calculated, and then the verisimilar false targets are generated. The effectiveness of the method is verified by simulation experiments.

Tracking multiple maneuvering targets hidden in the DBZ based on the MM-PHD filter

<p><a></a><a></a><a>For a ground moving target indication (GMTI) radar, the presence of </a><a></a><a></a><a></a><a>Doppler blind zone (DBZ)</a> results in many short tracks with frequent label switching, which seriously deteriorates the tracking performance. When the DBZ masking is coupled with targets maneuvering, tracking multiple maneuvering targets hidden in the DBZ becomes very challenging, which is reflected in the fact that there is no public research on this issue. To overcome this complicated problem, we propose a practical and fully functional GMTI multi-maneuvering-target tracker based on the multiple model probability hypothesis density (MM-PHD) filter. Unlike the standard MM-PHD filter, the proposed tracker utilizes the Doppler information and incorporates the minimum detectable velocity (MDV) to suppress the DBZ masking. Furthermore, to cope with the problems of the fixed initiation and no label output of the standard MM-PHD filter, the resulting MM-PHD filter with the Doppler and MDV information is augmented with measurement-driven adaptive track initiation and track label propagation, which are necessary for a practical tracker and also required for evaluating the overall GMTI tracking performance. Finally, numerical examples show that the proposed tracker outperforms significantly the existing ones, thus verifying its effectiveness.</p> <p> </p>

Tracking multiple maneuvering targets hidden in the DBZ based on the MM-PHD filter

<p><a></a><a></a><a>For a ground moving target indication (GMTI) radar, the presence of </a><a></a><a></a><a></a><a>Doppler blind zone (DBZ)</a> results in many short tracks with frequent label switching, which seriously deteriorates the tracking performance. When the DBZ masking is coupled with targets maneuvering, tracking multiple maneuvering targets hidden in the DBZ becomes very challenging, which is reflected in the fact that there is no public research on this issue. To overcome this complicated problem, we propose a practical and fully functional GMTI multi-maneuvering-target tracker based on the multiple model probability hypothesis density (MM-PHD) filter. Unlike the standard MM-PHD filter, the proposed tracker utilizes the Doppler information and incorporates the minimum detectable velocity (MDV) to suppress the DBZ masking. Furthermore, to cope with the problems of the fixed initiation and no label output of the standard MM-PHD filter, the resulting MM-PHD filter with the Doppler and MDV information is augmented with measurement-driven adaptive track initiation and track label propagation, which are necessary for a practical tracker and also required for evaluating the overall GMTI tracking performance. Finally, numerical examples show that the proposed tracker outperforms significantly the existing ones, thus verifying its effectiveness.</p> <p> </p>