Moving target indication

About: Moving target indication is a research topic. Over the lifetime, 2653 publications have been published within this topic receiving 32435 citations.

Technique for enhanced quality high resolution 2D imaging of ground moving targets

Abstract: A radar receiver on a moving platform images a moving target and non-moving clutter using a single SAR array. The radar receiver converts the radar returns into digital radar returns and motion compensates the digital radar returns with respect to a reference, then applies further phase compensation to obtain an autofocused synthetic aperture image. A plurality of moving target pixels descriptive of the moving target are detected within the autofocused synthetic aperture image. The plurality of moving target pixels are transformed from the autofocused image to the time domain. The time domain moving target data is focused by iteratively applying a phase compensation to the time domain moving target data.

Tracking of ground targets with bistatic airborne radar

Abstract: Detection of moving targets in stationary clutter can be accomplished by STAP radar. In contrast to monostatic radar the performance of bistatic STAP depends strongly on the actual radar-target geometry. Even for sidelooking radar the clutter Doppler is generally range dependent which causes special problems in estimating the space-time clutter covariance matrix. For certain bistatic constellations clutter notches as appearing during track (i.e. areas of low probability of detection) may be considerably wider than in monostatic radar. The bistatic transmitter-receiver constellation has strong implications on ground moving target tracking, which is basic for producing a recognized ground picture as well as for analyzing traffic flows, identifying sources and sinks of traffic, or detecting lines of communication. Aspects of a bistatic GMTI tracking algorithm are described and some typical tracking results are given. Special emphasis is placed on a suitable modeling of the bistatic radar characteristics within the tracker.

Spaceborne Interferometric and Multistatic SAR Systems

Abstract: This chapter analyses spaceborne multistatic imaging radar systems employing two or more receiver antennas on different platforms. The simultaneous data reception by multiple receivers enables a wealth of new synthetic aperture radar (SAR) imaging modes which evaluate the scattering signals from multiple view angles in combination. Potential application areas of multistatic SAR systems include, but are not limited to, single-pass cross-track and along-track interferometry, spaceborne tomography, wide swath SAR imaging, resolution enhancement, interference suppression, ground moving target indication (GMTI), and multistatic SAR imaging. Some of these applications can also be realized via multiple data acquisitions from repeat satellite passes. However, the simultaneous data acquisition with multiple satellites in a multistatic configuration avoids temporal decorrelation and atmospheric disturbances, improves the performance, and enables the detection of fast changes. This chapter gives a thorough overview of the capabilities and challenges associated with spaceborne interferometric and multistatic SAR missions. After a short introduction to interferometric SAR imaging, several design aspects are considered including phase and time synchronisation, formation and orbit selection, as well as the choice of suitable operational modes. The achievable performance is illustrated by the two mission examples TanDEM-X and TerraSAR-L cartwheel. An outlook on advanced multistatic SAR imaging modes illustrates their future potential for a wide range of remote sensing applications. The chapter is concluded with a discussion of major challenges to implement multistatic SAR missions in space.

Radar target detection in chaotic clutter

Abstract: The detection of targets in chaotic clutter is considered. Of particular interest in target detection is one of weak signal detection. The usual approach to signal detection amidst clutter is to model the clutter as a stochastic process with a certain probability distribution, for example, the K-distribution. The Bayesian approach to decision theory is then used to detect the presence of targets. It is assumed that sea clutter is a result of chaotic dynamics. This assumption leads to significant improvements in the processing gain of the receiver. The reason for this is that chaos has an underlying deterministic dynamics. Therefore, it permits a cancellation of the clutter at the receiver before performing target detection. The fundamental limit on performance is thus determined only by thermal noise and the accurate estimation of the underlying dynamical model. Results are shown for simple cases and the problem is discussed at length.