Sandia National Laboratories has teamed with General Atomics and Sierra Monolithics to develop the Athena tag for
the Army's Radar Tag Engagement (RaTE) program. The radar-responsive Athena tag can be used for Blue Force
tracking and Combat Identification (CID) as well as data collection, identification, and geolocation applications. The
Athena tag is small (~4.5" x 2.4" x 4.2"), battery-powered, and has an integral antenna. Once remotely activated by a
Synthetic Aperture Radar (SAR) or Moving Target Indicator (MTI) radar, the tag transponds modulated pulses to the
radar at a low transmit power. The Athena tag can operate Ku-band and X-band airborne SAR and MTI radars.
This paper presents results from current tag development testing activities. Topics covered include recent field tests
results from the AN/APY-8 Lynx, F16/APG-66, and F15E/APG-63 V(1) radars and other Fire Control radars. Results
show that the Athena tag successfully works with multiple radar platforms, in multiple radar modes, and for multiple
Radar-responsive tags such as Athena have numerous applications in military and government arenas. Military
applications include battlefield situational awareness, combat identification, targeting, personnel recovery, and
unattended ground sensors. Government applications exist in nonproliferation, counter-drug, search-and-rescue, and
Data collection for interferometric synthetic aperture radar (IFSAR) mapping systems currently utilize two operation modes. A single-antenna, dual-pass IFSAR operation mode is the first mode in which a platform carrying a single antenna traverses a flight path by the scene of interest twice collecting data. A dual-antenna, single-pass IFSAR operation mode is the second mode where a platform possessing two antennas flies past the scene of interest collecting data. There are advantages and disadvantages associated with both of these data collection modes. The single-antenna, dual-pass IFSAR operation mode possesses an imprecise knowledge of the antenna baseline length but allows for large antenna baseline lengths. This imprecise antenna baseline length knowledge lends itself to inaccurate target height scaling. The dual-antenna, one-pass IFSAR operation mode allows for a precise knowledge of the limited antenna baseline length but this limited baseline length leads to increased target height noise. This paper presents a new, innovative dual-antenna, dual-pass IFSAR operation mode which overcomes the disadvantages of the two current IFSAR operation modes. Improved target height information is now obtained with this new mode by accurately estimating the antenna baseline length between the dual flight passes using the data itself. Consequently, this new IFSAR operation mode possesses the target height scaling accuracies of the dual-antenna, one-pass operation mode and the height-noise performance of the one-antenna, dual-pass operation mode.
We describe an approach for inverse synthetic aperture radar (ISAR) imaging based on the Gabor wavelet transform. The Gabor basis function introduces three signal parameters which allow the components of a target signature to be mapped into a three-dimensional domain. Time, range, and frequency constitute the dimensions of this domain. Component distribution over the range and frequency dimensions corresponds to a snap shot of the target's scattering centers at a particular observation time. The snap shot resolution can be adjusted in each dimension by properly selecting the Gabor wavelet parameters. Parameter selection, as discussed in this paper, is used to minimize the quadratic phase distortion associated with moving target components. For multiple targets experiencing different velocities, selective motion compensation is incorporated to the Gabor wavelet transform approach, thus yielding focused imagery.
We describe three different processing approaches for stepped-frequency high-resolution radar that allow for the estimation of target motion parameters along the line of sight. Accurate knowledge of the motion parameters is necessary to generate a focused range-doppler image of the target. The approached adopted for this purpose are based upon the inverse discrete Fourier transform (IDFT), the modified chirp z-transform, and Prony's method. Estimates produced by these approaches are compared to each other as well as to the target's actual parameters. The IDFT approach, which is the standard procedure, requires zero padding to yield accurate estimates of the actual motion parameters and tends to be computationally intensive. The modified chirp z-transform approach yields accurate estimates with high computational efficiency for a wide SNR range. Prony's method proves to be a more robust approach for higher SNR. Considering these results, an MCZT adaptive algorithm for motion compensation is formulated which guarantees a well focused image.
Inverse synthetic aperture radar (ISAR) is an imaging technique that can be utilized in the identification of targets such as ships and aircraft. Since these targets are free to maneuver during the time required to collect their signature, kinematic motion parameter estimates are needed to focus ISAR imagery. In order to perform this estimation, a burst derivative measure, which has global minimum coordinates that provide optimum estimates of the motion parameters, is utilized in conjuction with unconstrained optimization algorithms. It is shown that the burst derivative is a multivariate function with a strong dependence on radar parameters. Results indicate that this dependence can be exploited by the optimization algorithms to obtain efficient motion estimation, thus improving the overall processing speed.
Three techniques for the motion compensation of wideband frequency-stepped signatures are compared. These approaches were developed with the intention of processing the signatures into focused range-Doppler images of moving targets. The approaches differ in three aspects: (1) the amount of Fourier processing; (2) the optimization process that yields the motion parameter estimates; and (3) the type of function utilized in the optimization process. Here, the emphasis is placed on the choice of a function that determines the motion parameters. The basic premise is that the function selected has a global minimum whose coordinates are the optimum estimates of the true motion parameters. In the first approach, the function is a measure of the entropy associated with the image. In the second approach, the function is a measure of the entropy associated with the range profile history from which the image is formed. In the third approach, the function is a measure of the rate of change of the target signature. A test case is offered to illustrate the properties of these functions. For this particular case, the performance of each motion compensation approach depends on the behavior of the corresponding function over a selected domain that includes the actual motion parameters of the target.