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.

Digital moving target indicator radar system incorporating modulo-n components

Abstract: A radar system is disclosed utilizing digital techniques for implementing a moving target indicator (MTI) or pulse doppler type of radar system. More specifically, the radar system includes an MTI filter or canceler circuit for suppressing clutter signals corresponding to stationary and/or relatively slow-moving targets, while providing an output signal indicative of echo signals received from relatively fast-moving targets. The canceling circuit of this invention achieves moving target detection with digital apparatus having a capability of processing only a limited number of digital bits. The MTI filter of this invention incorporates modulo-N components having a modulus or linear range so that the minimum detectable signal of interest lies therein. The higher magnitudes of signals corresponding to echo signals received from stationary and/or slowly-moving objects will be canceled by the canceling circuit, normally. If echo signals are developed from moving targets that are of higher magnitudes than the modulus, these signals will be ''''aliased'''' by the modulo-N components about the levels N/2 and N/2 to provide a noise-like output. Regardless of the amplitude of the echo signals derived from a relatively fast-moving target, detecting means is provided to detect the absence or presence of such signals.

Convoy detection processing by using the hybrid algorithm (GMCPHD/VS-IMMC-MHT) and Dynamic Bayesian Networks

Abstract: Convoys are military objects of interests in certain applications like battlefield surveillance, that is why it is important to detect and track them in the midst of civilian traffic as part of the situation assessment. Our purpose is a process in two steps. The first is an original tracking algorithm appropriate for Ground Moving Target Indicator (GMTI) data based on the hybridization of a labeled GMCPHD (Gaussian Mixture Cardinalized Probability Hypothesis Density) and the VS-IMMC-MHT (Variable Structure - Interacting Multiple Model with Constraints - Multiple Hypothesis Tracking): one is very efficient to estimate the number of targets and the other for the state estimates. Then, by using algorithm outputs and other data like video or SAR if they are available, vehicle aggregates are detected and their characteristic are introduced into a Dynamic Bayesian Network which processes the probability for an aggregate to be a convoy. Finally, the number of targets belonging to the convoy is evaluated. This process is tested on a complex simulated scenario, our tracking algorithm is compared to classical ones and used to compute the probability to have convoys.

MIMO radar target localization by using Doppler shift measurement

Abstract: A new method for target localization in MIMO radar is proposed. Localization of a moving, non-maneuvering target is possible by using Doppler-shift measurements and angle information in MIMO radar systems. This is a nonlinear problem and it must be solved for a grid search strategy. If the received frequencies and the angels between the target and the transmitter and the target and the receiver are known, we can search space grid by grid for desired (x, y) coordinates to find the position of the target in 2D space.

A Novel Algorithm For MIMO SAR Imaging

Abstract: A Multi-Input Multi-Output (MIMO) Synthetic Aperture Radar (SAR) system has been considered for its potential to simultaneously improve the performance of stationary scene imaging and ground moving target indication (GMTI) by utilizing multiple subarrays both at transmission and reception. To successfully exploit the potential benefits of MIMO SAR for practical imaging application, a signal model for MIMO SAR system with colocated arrays is presented in this paper, then we propose a novel procedure for imaging processing by coherently combining the returns from multiple receive subarrays. Our approach can make efficient use of the transmitted waveform power, and resulting in higher Signal-to-Noise Ratio (SNR) images. The effectiveness of model and MIMO SAR imaging method proposed in this paper are demonstrated by simulation experiments.