Coded space-time cooperation is an efficient approach in delivering information over a relay network. Multiple
cooperative terminals (nodes) form a distributed multiple-input-multiple-output (MIMO) systems, thus
providing high data rates and high diversity gains. However, unlike conventional co-located MIMO systems,
it is impractical for distributed MIMO networks to maintain perfect timing synchronization between different
transmit terminals. In particular, the presence of a fractional-symbol delay difference between the signals transmitted
from different terminals can cause erroneous sampling positions and yield highly dispersive channels even
at a memoryless channel environment. Existing methods solve such problem based on time-domain approaches
where adaptive equalization is required at the receivers for combining the information transmitted from distributed
sources. In this paper, we propose the use of OFDM-based approaches using distributed space-frequency
codes. The proposed schemes are insensitive to fractional-symbol delays and lead to higher data rate transmission
and simplified implementation. In addition, the proposed schemes permit the use of relatively simple
amplify-and-forward algorithm in multi-hop wireless networks without delay accumulations. The time delay in
each relaying hop by reconstructing the cyclic prefix and, as such, improve the spectral efficiency, while keeping
a simple relaying structure.
Signal space diversity is a power and bandwidth efficient diversity technique. To exploit the signal space diversity, joint maximum-likelihood (ML) detection at the receiver is usually needed, where the complexity grows expontentially with the dimension of a lattice. In this paper, we propose a serial concatenated scheme and two simple iterative methods to exploit the signal space diversity. The simple iterative methods are based on the idea of soft interference cancellation. The first iterative method is based on a scalar Gaussian approximation while the second one is a vector Gaussian approximation. The complexity of the first iterative method grows linearly with the dimension of the lattice, and the simulations show that when the dimension of the lattice <i>N</i> = 32, at BER = 10<sup>-5</sup>, the performance gap between the Rayleigh fading channel and the Gaussian channel is only 0.3 dB. The complexity of the second iterative method grows cubically with the dimension of the lattice and the simulations show that its performance approaches that of the optimal MAP detection method.
In over-the-horizon radar (OTHR) moving target detection, the signal to clutter ratio (SCR) is low. One method to detect a moving target is to first reject the clutter and improve the SCR before the detection, such as the adaptive Fourier transform developed by Root when a target moves uniformly. When a target does not move uniformly, the Fourier based techniques for the target detection including super resolution techniques may not work well. In this paper, we replace the Fourier transform by the adaptive chirplet transform in the Doppler processing in OTHR when a target moves non-uniformly.
This paper first reviews some basic properties of the discrete chirp-Fourier transform and then present an adaptive chirp- Fourier transform, a generalization of the amplitude and phase estimation of sinusoids (APES) algorithm proposed by Li and Stoica for sinusoidal signals. We finally applied it to the ISAR imaging of maneuvering targets.
Detection, location and SAR imaging of moving targets in clutter have attracted much attention. Locations of moving targets in the SAR image are determined not only by their geometric locations but also by their velocities that cause their SAR images de-focused, smeared, and mis-located in the azimuth dimension. Furthermore, the clutters may cause the detection of moving targets more difficult. Several antenna array based algorithms have been proposed to re-locate the moving targets in the SAR image. With a linear antenna array, the clutters may be suppressed using multiple phase centers. However, there are only two parameters involved in a linear antenna array, i.e., number of receiving antennas and the distance between two adjacent antennas. These two parameters physically limit the capability to detect the accurate locations of fast moving targets and such as vehicles, and only slowly moving targets, such as walking people, can be correctly re-located. In this paper, we propose an antenna array approach where transmitting single wavelength signals are generalized to transmitting multiple wavelength signals (called multi-frequency antenna array SAR). We show that, using multi-frequency antenna array SAR, not only the clutters can be suppressed but also locations of both slow and fast moving targets can be accurately estimated. For example, using two-frequency antenna array SAR system with wavelengths (lambda) <SUB>1</SUB> equals 0.03 m and (lambda) <SUB>2</SUB> equals 0.05 m, the maximal moving target velocity in the range direction is 1 5 m/s while using single frequency antenna array SAR system with wave length (lambda) <SUB>1</SUB> equals 0.03 m or (lambda) <SUB>2</SUB> equals 0.05 m, the maximal moving target velocity in the range direction are 3 m/s or 5 m/s, respectively. A robust Chinese Remainder Theorem (CRT) is developed and used for the location of fast and slowly moving targets. Simulations of SAR imaging of ground moving targets are presented to illustrate the effectiveness of the multi-frequency antenna array SAR imaging algorithm.
Amin et. al. recently developed a time-frequency MUSIC algorithm with narrow band models for the estimation of direction of arrival (DOA) when the source signals are chirps. In this research, we consider wideband models. The joint time-frequency analysis is first used to estimate the chirp rates of the source signals and then the DOA is estimated by the MUSIC algorithm with an iterative approach.
Friedlander and Porat recently presented velocity SAR (VSAR) imaging of moving targets. In this correspondence, the VSAR is generalized to multi-frequency VSAR (MFVSAR). The MFVSAR can image both slowly and fast moving targets. Simulation results are presented to illustrate the theory.
In conventional synthetic aperture radar (SAR) systems, the image of a moving target is usually mislocated. In this paper, a dual-speed SAR imaging approach, i.e., the radar platform flies with two different speeds in the radar observation time duration, is proposed to resolve the above two problems, especially the mis-location problem. We also propose several practical approaches to the realization of the dual-speed radar platform. Some simulation results are given.
The non-ideal motion of the hydrophone usually induces the aperture error of the synthetic aperture sonar (SAS), which is one of the most important factors degrading the SAS imaging quality. In the SAS imaging, the return signals are usually nonstationary due to the non-ideal hydrophone motion. In this paper, joint time-frequency analysis (JTFA), as a good technique for analyzing nonstationary signals, is used in the SAS imaging. Based on the JTFA of the sonar return signals, a novel SAS imaging algorithm is proposed. The algorithm is verified by simulation examples.
Chen recently presented an ISAR imaging technique using the joint time-frequency analysis (JTFA), which has been shown having a better performance for maneuvering targets over the conventional Fourier transform method. It is because the frequencies of the radar returns of the maneuvering targets are time-varying and JTFA is a technique that is suitable for such signals. It is also known that JTFA concentrates a signal, such as a chirp, while spreads noise. In this paper, we study the signal-to-noise ratio (SNR) in the ISAR imaging using the JTFA. We show that the SNR increases in the joint TF domain over the one in the time or the frequency domain alone both theoretically and numerically. This shows another advantage of the JTFA technique for the ISAR imaging.