Target classification for air defence radars

A concept for a Multi-Function Phased Array Radar (MPAR) to provide next generation simultaneous aircraft and weather surveillance has been developed. This paper discusses a number of system design considerations that are needed to address the multi-mission challenges of MPAR, especially with respect to its stringent timeline objectives.

Multi-sector arrays have been used for decades, including applications on ships, aircraft, vehicles, and ground-based platforms. In most of these applications, however, spatial isolation generated through the use of strategic sector placement has provided sufficient overall isolation between each sector. The United States has recently been exploring the potential for a multi-function phased array radar (MPAR) network that would provide surveillance, tracking, and detection capabilities for the nation's weather, terminal weather, and national airspace missions. Several studies have assumed a multi-sector approach on a single platform. With the goal of allowing each sector to independently operate, concerns regarding isolation between the sectors have introduced the desire to gain additional isolation through waveform design. Recent advances in frequency-modulated pulse compression techniques have afforded the ability to maximize sensitivity and sidelobe performance within a given time-bandwidth specification; however, waveform design has the potential to bring numerous other spectral efficiency advancements to the MPAR mission. A generalization of recent waveform design techniques into a multi-sector waveform group is presented. Simulations of a four-sector waveform group are carried out and optimized for minimal interference. The ability to achieve high waveform-based isolation is combined with varying spatial isolations and slight frequency offsets to drastically reduce overall spectrum usage for a multi-sector array.

A simulation test bed is presented which operates in non-real-time to provide full-scale simulation of ground- and ship-based multifunction phased array radars. This simulation test bed provides capability to design and evaluate the performance of different radar resource management, target tracking and beam-forming algorithms. Model of radar is presented which includes radar antenna, signal and data processing and radar manager. Simulated environment consists of different target models and trajectories, electronic warfare threats and environmental effects. Signal simulation is explained which includes target echo, multipath, noise, clutter and different techniques of jamming. Some results are presented that show capabilities of this simulation software for multifunction radar algorithms design and performance evaluation.

This paper describes a semiautonomous approach to calibrate a phased array system, with particular use on an S-band aperture that is being developed at MIT Lincoln Laboratory. Each element of the array is controlled by an independent digital phase shifter, whose control signal may be uniquely defined. As active electronically steerable arrays (AESAs) continually evolve towards mostly digital paradigms that will support real-time computing, as opposed to look-up table approaches, then adaptive calibration approaches may be pursued for maximum AESA performance. This calibration work is being completed as one component of Lincoln Laboratory's effort within the multifunction phased array radar (MPAR) initiative.

The problem of minimizing dwell time in multifunction phased array radar is considered. Target of interest is assumed to fluctuate according to a generalization of Swerling family and the parameters of fluctuation model are assumed to be known. The a'priori position of the target is uncertain. Optimization, whose variables include pulse count and array transmit beampattern, is carried out subject to achieving a desired accuracy of angular coordinate estimates.

<p>Inverse Synthetic Aperture Radar images are playing a significant role in classification of sea and air targets. First we acquire the ISAR images of targets using a sensor like radar and extract the characteristics of targets from the ISAR images in the form of feature vectors. The computed feature vectors are used for classification of targets. In this work, widely used and efficient segmentation tool Watershed transform and the multi resolution technique wavelet transform are explored to derive the target features. An artificial neural network based classifier is used for classification. The Wavelet analysis divides the information of an image into approximation and detail sub signals. The approximate and three detail sub signal values are taken as feature vectors and given as input to the classifier for ship ISAR image classification. The widely used segmentation technique, Watershed transform is applied to the ISAR images. The wavelet coefficients are computed for the segmented ISAR images and used as feature vectors for classification of the ISAR images. Also, the statistical moments mean and standard deviation are computed for the color ISAR images itself, taken in RGB format. These statistical color moments are used as feature vector. The classification accuracy is compared for the feature vectors.</p>

MIT Lincoln Laboratory is working towards the development of a tileable radar panel to satisfy multimission needs. A combination of custom and commercial off-the-shelf (COTS) Monolithic Microwave Integrated Circuits (MMICs) have been developed and/or employed to achieve the required system functionality. The integrated circuits (ICs) are integrated into a low cost T/R module compatible with commercial printed circuit board (PCB) manufacturing. Sixty-four of the transmit/receive (T/R) modules are integrated onto the aperture PCB in an 8 × 8 lattice. In addition to the T/R elements, the aperture PCB incorporates transmit and receive beamformers, power and logic distribution, and radiating elements. The aperture PCB is coupled with a backplane PCB to form a panel, the line replaceable unit (LRU) for the multifunction phased array radar (MPAR) initiative. This report summarizes the evaluation of the second iteration LRU aperture PCB and T/R element. Support fixturing was developed and paired with the panel to enable backplane functionality sufficient to support the test objectives.

The Configurable Phased Array Demonstrator (CPAD) is a low-cost, reconfigurable, small scale testbed for dual-polarized phased array antenna prototype. It is based on the concept that individual TR modules and radiating elements can be configured in different ways to study the impact of array manifolds on the radiation pattern performance. As an example, a 4 by 4 planar array was constructed with CPAD to support the Multi-Functional Phased Array Radar (MPAR) system developments, and the initial simulation and measurement results of this system are compared.

High range resolution (HRR) has many advantages in ground penetrating radar (GPR) [1]. Apart from providing the ability to resolve closely spaced targets in range, it improves range accuracy, reduces the amount of clutter within resolution cell, reduces multipath, provides high resolution profiles and aids in target classification. HRR provides characteristic features of objects, for example parameters connected with physical dimensions or shape. In the paper one of superresolution methods of obtaining unambiguous synthetic range profiling in SFCW radar was described. A method for eliminating signals from possible false targets generated by overestimation of number of actual targets in MUSIC algorithm was discussed.

Unique observations of the interaction and likely merger of two cyclonic tornadoes are documented. One of the tornadoes involved in the interaction was the enhanced Fujita scale (EF5) El Reno–Piedmont, Oklahoma, tornado from 24 May 2011 and the other was a previously undocumented tornado. Data from three S-band radars: Twin Lakes, Oklahoma (KTLX); Norman, Oklahoma (KOUN); and the multifunction phased-array radar (MPAR), are used to detail the formation of the second tornado, which occurred to the northwest of the original tornado in an area of strong radial convergence. Radar data and isosurfaces of azimuthal shear provide evidence that both tornadoes formed within an elongated area of mesocyclone-scale cyclonic rotation. The path taken by the primary tornado and the formation location of the second tornado are different from previous observations of simultaneous cyclonic tornadoes, which have been most often observed in the cyclic tornadogenesis process. The merger of the two tornadoes occurred during the sampling period of a mobile phased-array radar—the Mobile Weather Radar, 2005 X-Band, Phased Array (MWR-05XP). MWR-05XP electronic scanning in elevation allowed for the merger process to be examined up to 4 km above radar level every 11 s. The tornadic vortex signatures (TVSs) associated with the tornadoes traveled around each other in a counterclockwise direction then merged in a helical manner up through storm midlevels. Upon merging, both the estimated intensity and size of the TVS associated with the resulting tornado increased dramatically. Similarities between the merger observed in this case and in previous cases also are discussed.

In this paper, a system-specific phased-array radar system simulator was developed, based on a time-domain modeling and simulation method, mainly for system performance evaluation of the future Spectrum-Efficient National Surveillance Radar (SENSR). The goal of the simulation study was to establish a complete data quality prediction method based on specific radar hardware and electronics designs. The distributed weather targets were modeled using a covariance matrix-based method. The data quality analysis was conducted using Next-Generation Radar (NEXRAD) Level-II data as a basis, in which the impact of various pulse compression waveforms and channel electronic instability on weather radar data quality was evaluated. Two typical weather scenarios were employed to assess the simulator’s performance, including a tornado case and a convective precipitation case. Also, modeling of some demonstration systems was evaluated, including a generic weather radar, a planar polarimetric phased-array radar, and a cylindrical polarimetric phased-array radar. Corresponding error statistics were provided to help multifunction phased-array radar (MPAR) designers perform trade-off studies.

Aiming at imaging task scheduling of multifunction phased array radar, this paper puts forward an adaptive scheduling algorithm for ISAR imaging radar based on pulse interleaving. Firstly, required resources for sparse aperture ISAR imaging were calculated according to initial cognition of target feature, based on that, a rational and optimized scheduling model of interleaving pulse dwelling is established, then radar resources can be allocated reasonably under the dual restraints of time and energy. At last, different targets were imaged respectively using compressed sensing-based sparse aperture ISAR imaging method and required imaging resolution is achieved while resource utilization rate is enhanced apparently. The simulation testified the feasibility of this algorithm.

In this study, the support vector machine (SVM) was used as a classifier to identify aerospace objects. Radar target identification based on high resolution range profiles (HRRPs) received much attention because of its reduced complexity than those using two-dimensional (2-D) ISAR images. Therefore range profiles were used as feature vectors to represent radar data. Data sets which are for training and testing were generated by using a program called radar target backscattering simulation (RTBS) for three different target types. The performance of the SVM was compared with other classification algorithms including statistical classification techniques such as maximum likelihood (ML) and fisher linear likelihood (FLL).

ISAR imaging has potential in assisting with the classification of non-cooperative targets. Blurred ISAR imagery may however lead to misleading classification results. Much research has been done to understand some of the causes of distortion in ISAR imaging mostly under the limited assumption that a target's axis of rotation is constant over the CPI. This paper investigates how the target's time-varying Doppler generating axis of rotation, caused by the complex 3D motion of a target at sea, contributes to ISAR image blurring. Quaternion algebra is used to aid the characterisation of a time-varying Doppler generating axis of rotation on the migration through cross-range cells. Real motion data of a sailing yacht is used to examine the effects of 3D rotational motion on ISAR imagery of point scatterer like simulated targets and the associated blurring. Simulation results show that small yaw rate perturbation during side-view ISAR imaging intervals gives rise to significant changes in the direction of the Doppler generating axis which results in scatters migration through cross-range cells. (5 pages)

In this paper we employ evolutionary algorithms for the selection of optimal pulse repetition frequency (PRF) sets to minimise range-Doppler blindness in a model of a medium PRF radar. Both eight and nine PRF schedules are considered and the algorithm ensures that all the solutions produced are fully decodable and have no blind velocities. We consider the detailed effects of side-lobe clutter and the many technical factors affecting the choice of radar PRF in a medium PRF mode of operation of a practical airborne fire control radar.