2.1 Syntheticaperture assessment of a dispersive surface
By: Margaret Cheney
RPI

This paper considers syntheticaperture radar and other
syntheticaperture imaging systems in which a backscattered
wave is measured from a variety of locations. We consider the case
in which the reflections take place on a known surface, but
the reflection at a particular point depends on frequency.
The ability to determine a frequencydependent
reflectivity function may aid in the characterization of materials. 
2.2 ISAR minimumentropy phase adjustment
By: Junfeng Wang
Shanghai Jiaotong University
and: Xingzhao Liu
Shanghai Jiaotong University

A new technique is developed for phase adjustment in ISAR imaging. The adjustment phase is found by iteratively solving an equation, which is derived by minimizing the entropy of the image. This technique can be used to estimate adjustment phases of any form. Moreover, the optimization method used in this technique is computationally more efficient than trialanderror methods. 
2.3 Developments in repeat pass interferometric radar for earth and planetary sciences
By: Paul Rosen
JPL

Repeat pass radar interferometry has developed into a wide ranging geodetic and change mapping tool from space. For large areas of the Earth, and for numerous applications that demand more persistent monitoring, the true potential of the repeat pass technique remains largely untapped. While the research community has made enormous strides in extracting as much information as possible from existing data sets, fundamentally new observing systems are needed for breakthroughs in a number of areas. Repeat pass interferometry techniques applied on missions to the terrestrial planets, Earth?s moon and the icy moons of Jupiter can reveal new insights in to the history of the surface and near subsurface. 
2.4 An inverse polar format algorithm for turntable spotlight ISAR imaging systems using stepped frequency waveforms
By: Scott D. Fisher
Georgia Institute of Technology
and: Mark A. Richards
Georgia Institute of Technology
and: Gregory A. Showman
Georgia Tech Research Institute

Basic turntable spotlight inverse synthetic aperture radar (ISAR) systems that employ stepped frequency waveforms implement image formation algorithms based on the premise that data collection over uniform frequency and angle steps results in a rectangular sampling of the image spatial frequency (kspace) domain. As a result, a simple image formation algorithm implementing only a computationally efficient inverse 2D discrete Fourier transform (DFT) may be realized. However, this approach imposes limitations on resolution and/or scene size since the conventional data collection procedure actually results in a polar sampling of kspace, invalidating the rectangular grid assumption. This paper introduces a new data collection scheme using stepped frequency waveforms that are nonuniformly stepped in time and frequency so as to collect sample points according to the desired kspace shape. This procedure allows the use of a single inverse 2D DFT as the image formation algorithm, thereby reducing traditional constraints on resolution and scene size while maintaining good image focus and reducing computational complexity. 
2.5 Enhanced maneuvering targets detection via polynomial phase modeling in overthehorizon radar
By: Kun Lu
Shanghai Jiao Tong University
and: Xingzhao Liu
Shanghai Jiao Tong University

This paper describes a processing algorithm based on polynomial phase modeling scheme that increases visibility of maneuvering targets in HF overthehorizon radar (OTHR). For the presence of the echo backscattered by the target that has significantly varying radial velocity within a coherent integration time (CIT), it is difficult for traditional coherent processing to centralize energy and peak in Doppler spectrum. Due to the polynomial property of the phase of maneuvering target radar echo, a polynomial phase signal (PPS) is introduced to model the complex Doppler variation of maneuvering targets. As an effective method to estimate the parameters of PPS, highorder ambiguity function (HAF) based algorithm is applied. And a compensation process follows to eliminate the coherent processing loss (CIL) caused by irregular motion of targets. The experimental results are given to illustrate the validity and efficiency of the proposed method. 
2.6 Detection and tracking of ballistic target
By: Alfonso Farina
AMS
and: Luca Timmoneri
AMS
and: Maria Rosaria Toma
AMS
and: Luciana Ortenzi
AMS
and: Ugo Fabrizio D'Elia
MBDA Italy
and: Maria Grazia Del Gaudio
MBDA Italy
and: Sandro Immediata
AMS

Some aspects of detection and tracking of ballistic targets are analysed in this paper. In particular, the RCS model versus aspect angle is obtained for a notional target starting from its CAD model. Subsequently, the kinematic model of the ballistic target is derived; it includes the main forces acting on it, namely: the thrust, the drag and the gravity. On the basis of these two models it is possible to determine the detection probability of a notional Lband radar during the target flight and to build up an interactive multiple model (IMM) for target tracking. The performance evaluation of the design IMM tracking algorithm is obtained via Monte Carlo simulation. In particular, highly manoeuvring aircraft and ballistic target in the boost phase are used to check the capability of the IMM. 
2.7 A Kalman filterbased radar track data fusion algorithm applied to a select ICBM case
By: John G Ferrante
Lockheed Martin MS2 Moorestown Advanced Systems

A Kalman filterbased approach to fusing track data from two separate phased array radar sensors is developed and applied to a select ICBM case to demonstrate the potential enhancement of position and velocity estimates over a single radar. When compared to a theoretical assessment based on steady state filter performance, the Kalman filter approach yielded performance enhancements within 7% of theoretical prediction. The theoretical assessment indicated a 33% improvement in position accuracy and a 29% improvement in velocity accuracy for an assumed bias error in both radars. The simulation yielded a 29% improvement in position accuracy and a 22% improvement in velocity accuracy with the same bias assumption. The improvement was computed relative to the radar with twice the beamwidth and the same sensitivity as the second ?fused? radar. The two radars were assumed to be collocated at the terminal area of ICBM flight.
The simulated estimates were obtained by a Monte Carlo approach which averaged the results of simulation runs of fused and single radar position and velocity estimates of a known ICBM trajectory. The trajectory was generated by solving the matrix differential equations of motion for both the exo and endoatmospheric portions of the ICBM flight. MATHCADbased simulations incorporating trajectory generation and track data fusion algorithms were developed to perform the described analyses.

2.8 Effect of the common process noise on performance of twosensor fusedtrack
By: Jie Zhao
School of Automatic, Northwestern Polytechnical University
and: Tao Xu
Lab.551, Dept. of E.E., Beijing Institute of Technology
and: LiXiang Ren
Lab.551, Dept. of E.E., Beijing Institute of Technology
and: Zhishe Cui
Missile College, Air Force Engineering University

This paper presented effect of the common process noise on track statistical distance and performance of state estimation fusion. Because of great computational load on crosscovariance matrix produced by process noise, indeed, which is a half of total computational load, thus realtime computation of crosscovariance matrix is avoided in system implement. First, computational load on crosscovariance matrix, track statistical distance, and state estimation fusion are estimated and compared. And effect of the common process noise on track statistical distance and performance of state estimation fusion are simulated. Simulation results show that in the case of less process noise, crosscovariance matrix is neglected, whereas it cannot. 