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.

Radar Target Detection and Map-Matching Algorithm Studies

Abstract: Results of a study of adaptive threshold target detection and map-matching algorithms are presented. Log threshold processing is shown to be preferred over linear threshold processing when the clutter data surrounding the target cell is contaminated by other targets, decoy corner reflectors, or bright clutter cells. Whereas previous studies have resorted to extensive Monte-Carlo simulations of log threshold algorithms, the results were obtained using a novel analytical approach based upon Parseval's theorem.

L-band SBR moving target detection in SAR-GMTI modes

Abstract: Space Based Radars (SBR) are being considered for a wide range of area surveillance tasks due to the global, all weather capability to image and detect moving targets. SBR has the capability of detecting either slow moving ground targets or high speed airborne targets, in addition to the familiar synthetic aperture radar (SAR) imaging mode. However, due to the high satellite velocity and long wavelength of an L-band SBR, detection of slow moving targets is very difficult. Two radar modes are being considered: Multiple-Channel Ground Moving Target Indication Space Time Adaptive Processing (GMTI STAP), and Along Track Interferometry (ATI) SAR. The system implications and mode requirements are reviewed for efficient wide area surveillance.

On parametric detection of small targets in sea clutter

Abstract: A new algorithm is presented that instantaneously estimates the clutter characteristics in the environment of the radar cell that is processed. No a priori information is used, since the algorithm operates directly on the data of the incoming burst. It is a technique that adapts continuously and instantaneously to the environment. The algorithm, after having identified the sea clutter rejects this sea clutter from the data; thus enhancing the probability of detecting small objects in a clutter environment. The final step is the actual detection that makes use of the advantages of the parametric representation. This results in a lower rate of false detections and as a consequence the later stages, like clustering and tracking, receive a more accurate input. The technique behind this algorithm uses recent developments in parametric time series analysis and performs well in suppressing sea as well as land clutter.

Detecting and tracking of small moving target under the background of sea level

Abstract: Target detecting and tracking based on video is one of the significant research field of computer vision, in this paper some research has been done on the small moving target under the background of sea level. In the process of target detecting, the moving targets detecting algorithm combining the method of background subtraction with the method of symmetrical difference is proposed in this paper. In the process of target tracking, using mean shift combining Kalman filter. Kalman filter can predict the possible position on the next frame of the video image, and using the mean shift algorithm to search in this neighboring range, this method is effective on fast moving target. The experiment shows that itpsilas a good algorithm to track the small target in the circumstance of low signal noise rate.

Test results from the AN/APY-6 SAR/GMTI surveillance, tracking and targeting radar

Abstract: The AN/APY-6 is an X-band radar developed by Northrop Grumman under ONR (Office of Naval Research) sponsorship. It was developed to provide all-speed target detection, location, tracking, imaging and exploitation. It was installed in a USA Navy NP-3 aircraft in July 1999 and continues to undergo testing and demonstration in the NP-3. This paper presents test results in the form of SAR, GMTI and tracking imagery obtained from programs in which the NP-3 has participated. These include the DARPA Affordable Moving & Stationary Target Exploitation (AMSTE) GMTI precision location program and a number of USN fleet battle exercises (FBE) and the NATO Clean Hunter 2000 exercises.