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.

Method and radar system for coherent detection of moving objects

Abstract: The present invention provides a coherent radar system based on a modification of standard non-coherent radar without Moving Target Indication. Typical radars in this class are Navigation radars which are mass produced with low cost components. These radars utilize a magnetron in the transmitter which is a random phase device. In the present invention, the received signal is extracted just prior to amplitude detection process (where phase information is lost), and digitized using an analogue to digital converter providing coherent detection based on correlation between the transmitted pulse and the received signal.

Method of determining the velocity of a radar target

Abstract: A method of determining the velocity of a radar target wherein at least two different pulse repetition frequencies are used. Each pulse repetition frequency comprises a predetermined division into equidistant Doppler numbers. For an echo signal, a Doppler number associated with the echo signal is determined for each pulse repetition frequency. Out of two Doppler numbers associated with different pulse repetition frequencies, a nonambiguous Doppler number is subsequently determined which lies within a predetermined velocity nonambiguity range, and the velocity of the radar target is determined from this Doppler number.

Target identification from a pool of targets using a new adaptive transmitter-receiver design

Abstract: A design methodology for jointly optimizing the transmit waveform and receiver filter for multiple target identification is presented in presence of transmit signal dependent clutter like interference and noise. The methodology is applied and illustrated for various multiple ‘target ID’ problems in presence of transmit signal dependent clutter like interference and noise. The resulting correct target classification is significantly better than that achieved by a conventional chirp or any other transmit waveform. Unlike the classical radar case, the choice of transmit pulse shape can be critically important for the detection of extended targets in presence of additive channel noise and signal-dependent clutter.

A real-time effective method for infrared point-target detection in spatially varying clutter

Abstract: This paper presents an algorithm of designing an effective image sequence processing scheme, which based on analyzing the targets and background model correctly. This algorithm will successfully detect very small (point) target in spatially varying clutter background when both the target and clutter are moving through the image scene. This method focuses on reducing the cost of computation, tracking the target in real-time, enhancing the SNR, and suppressing the clutter.

Robust space-time adaptive processing for nonhomogeneous clutter in the presence of model errors

Abstract: In this paper, we first develop a novel array self-calibration method for estimating array gain-phase errors by computing the clutter subspace from the radar system parameters and using the clutter data in space-time adaptive processing (STAP). The proposed algorithm is shown to perform well even in nonhomogeneous clutter, and it can improve the performance of existing STAP algorithms, such as the clutter subspace-based method in the presence of array gain-phase errors.We also develop a two-stage STAP approach for suppressing nonhomogeneous clutter in the presence of model errors in addition to array gain-phase errors. In our two-stage STAP approach, the first stage explores the clutter subspace calculated from the radar system parameters to suppress the main clutter. The second stage employs the conventional method, such as the partially adaptive sample matrix inversion STAP method, to remove any residual clutter. Numerical results illustrate the benefits of the array self-calibration method and the effectiveness of the two-stage STAP method. Finally, the performance of the three STAP methods is compared via the well-known MCARM data set. The results further confirm that there is an improvement in performance when using array self-calibration together with the two-stage STAP method.