Adaptive Moving Target Indication Research Articles

An Improved Segmented MTI Filter Based on a Clustering Algorithm

A K-Means clustering algorithm modified MTI (Moving Target Indication) filter is proposed for refining signal processing of the array environment in response to the current demand for clutter suppression by array adaptive technology. The method first uses the clutter distribution type and distance as parameters of the K-Means clustering algorithm to divide the echo’s into different clutter distance segments. Then an adaptive MTI filter is used to filter each clutter distance segment separately. The identification was carried out using measured ground radar echo data. The results show that the k-means clustering algorithm has better clutter distance segmentation capability. Compared with the conventional two-pulse MTI filter, the improved segmented MTI filter of the k-means algorithm has better clutter suppression in complex clutter environments.

Signal Processing and Target Fusion Detection via Dual Platform Radar Cooperative Illumination

A modified signal processing and target fusion detection method based on the dual platform cooperative detection model is proposed in this paper. In this model, a single transmitter and dual receiver radar system is adopted, which can form a single radar and bistatic radar system, respectively. Clutter suppression is achieved by an adaptive moving target indicator (AMTI). By combining the AMTI technology and the traditional radar signal processing technology (i.e., pulse compression and coherent accumulation processing), the SNR is improved, and false targets generated by direct wave are suppressed. The decision matrix is obtained by cell averaging constant false alarm (CA-CFAR) and order statistics constant false alarm (OS-CFAR) processing. Then, the echo signals processed in the two receivers are fused by the AND-like fusion rule and OR-like fusion rule, and the detection probability after fusion detection in different cases is analyzed. Finally, the performance of the proposed method is quantitatively analyzed. Experimental results based on simulated data demonstrate that: (1) The bistatic radar system with a split transceiver has a larger detection distance than the single radar system, but the influence of clutter is greater; (2) the direct wave can be eliminated effectively, and no false target can be formed after suppression; (3) the detection probability of the bistatic radar system with split transceivers is higher than that of the single radar system; and (4) the detection probability of signal fusion detection based on two receivers is higher than that of the bistatic radar system and single radar system.

Optimization of Adaptive MTI Filter

Moving target indication (MTI) is an effective means for radar to find moving targets in clutter environment. This paper introduces the basic principles of MTI, how to avoid the blind speed problem and the optimization of MTI filter. Implementing the multi-notch adaptive moving target indication (AMTI) filter that designed by using the stagger code in varied cases, which is based on a feature vector method optimization.

Adaptive moving target indication in a windblown clutter environment

The statistical properties of windblown grass and forest clutter, obtained using high-resolution microwave Doppler radar, are analyzed and shown to be nonstationary. In particular, we show that the bandwidth of the Doppler signal depends linearly on the total power of the signal for both types of vegetation. Also, variations in the mean power and spectrum bandwidth of the clutter are similar to the analysis time of existing radars. The model of an adaptive moving target indication (MTI) notch filter is presented and evaluated. It is shown that adaptive filtering significantly improves the efficiency of an MTI system.

Improvement of Automated Identification of the Heart Wall in Echocardiography by Suppressing Clutter Component

For the facilitation of analysis and elimination of the operator dependence in estimating the myocardial function in echocardiography, we have previously developed a method for automated identification of the heart wall. However, there are misclassified regions because the magnitude-squared coherence (MSC) function of echo signals, which is one of the features in the previous method, is sensitively affected by the clutter components such as multiple reflection and off-axis echo from external tissue or the nearby myocardium. The objective of the present study is to improve the performance of automated identification of the heart wall. For this purpose, we proposed a method to suppress the effect of the clutter components on the MSC of echo signals by applying an adaptive moving target indicator (MTI) filter to echo signals. In vivo experimental results showed that the misclassified regions were significantly reduced using our proposed method in the longitudinal axis view of the heart.

An adaptive moving target indicator using median filters

An adaptive moving target indicator, AMTI, is a filter that automatically suppresses the moving clutter contained in a received radar signal. In AMTI based on an adaptive filter, the amplitude and the phase of the filter weight are simultaneously adjusted and this enhances the effect of the adaptation error. For this problem, this paper proposes weight-magnitude-constrained AMTI, where only the phase of the filter weight is adjusted in real-time as a parameter in order to improve clutter suppression performance. We then consider an environment in which the power of the desired signal is not negligible compared to the clutter power. In order to reduce the estimation error for the clutter center frequency, weight-magnitude-constrained AMTI introducing a median filter is proposed. The effectiveness of this approach is demonstrated by computer simulation. A situation is considered, where the received noise is modulated by a moving target indicator (MTI) that suppresses the static clutter in AMTI pre-processing; an algorithm for clutter center frequency estimation is presented for which the estimation accuracy is guaranteed. © 1998 Scripta Technica. Electron Comm Jpn Pt 1, 81(5): 41–50, 1998

The analysis of compatible system of AMTI and SAR

Based on the analysis of Adaptive Moving Target Indication (AMTI) and the signal processing of Synthetic Aperture Radar(SAR), a complete compatible system of AMTI and SAR is put forward. The compatibility and effectiveness of this system is proved in theory. The results of simulation show that this system not only has good ability in stationary targets imaging but also has ability in detecting moving targets under the background of strong clutter.

Simulation of an adaptive MTI in a monopulse FMCW radar sensor

A range-doppler spread target model is modified to obtain a clut ter model by including the effect of beam and range gate shape. This clutter modeling is then applied in a simulation of an FMCW radar sensor that uses an adaptive moving target indicator (AMTI) and a monopulse antenna to detect slow-moving ground targets. The ability of the AMTI to discriminate a slow-moving point target from ground clutter is shown via simulation.

Clutter Covariance Matrix Form Effect on Adaptive MTI Performance

The performance of an adaptive moving target indicator (MTI), which employs a Wiener predictor by means of a transversal filter, is discussed, taking into consideration the effect of the form of the clutter covariance matrix on the MTI performance. It is emphasized that the main tap position in the transversal filter is an important factor which provides degrees of freedom in the clutter covariance matrix to improve the MTI performance. Calculation results show that by exploiting these degrees of freedom, excellent performance is feasible, in particular shorter transient response.

Design and Evaluation of an Adaptive MTI Filter

The design and evaluation of an adaptive moving target indicator (MTI) filter, the adaptive canceler for extended clutter (ACEC) is dealt with, taking into consideration adaptivity to clutter mean Doppler frequency. This consideration is one of the most important operational requirements in adaptive MTI's and permits a relatively simple hardware implementation as compared to more general optimization and adaptivity criteria (briefly described). The ACEC's algorithm compensates in real time for the clutter mean Doppler frequency. Performances have been obtained by digital computer simulation in various operational conditions.