Radar matched filtering using the fractional fourier transform

Abstract-A matched filter is the optimal linear filter for maximizing the signal to noise ratio (SNR) in the presence of additive noise. Matched filters are commonly used in radar systems where the transmitted signal is known and may be used as a replica to be correlated with the received signal which can be carried out by multiplication in the frequency domain by applying Fourier Transform (FT). Fractional Fourier transform (FrFT) is the general case for the FT and is superior in chirp pulse compression using the optimum FrFT order. In this paper a matched filter is implemented for a chirp radar signal in the optimum FrFT domain. Mathematical formula for a received chirp signal in the frequency domain and a generalized formula in the fractional Fourier domain are presented in this paper using the Principle of Stationary Phase (PSP). These mathematical expressions are used to show the limitations of the matched filter in the fractional Fourier domain. The parameters that affect the chirp signal in the optimum fractional Fourier domain are described. The performance enhancement by using the matched filter in the fractional Fourier domain for special cases is presented

SAR image registration in the presence of rotation and translation : a constrained least squares approach

This letter proposes a coregistration algorithm to compensate for possible inaccuracy of trajectory sensor during the SAR image acquisition process. Such a misalignment can be modeled as a pure displacement in range and azimuth directions and a rotation effect due to different angle of sight. The approach is formalized as a Constrained Least Squares (CLS) optimization problem enforcing a constraint of absence of a zooming effect between the two SAR images. Moreover, system equations can optionally be weighted according to local properties between the extracted patches within the quoted couple. Interestingly, the solution can be obtained in closed-form, therefore with a low computational cost. The results of the tests conducted on the 9.6GHz Gotcha SAR data demonstrate the capability of the strategy to proper register the imagery

Understanding the potential of Self-Protection Jamming on board of miniature UAVs

Unarmed Aerial Vehicle (UAV) systems are very challenging targets due to their small size and ability to fly in low altitudes and speed. Particularly, in radar systems UAVs can exhibit similar radar cross section and Doppler parameters to clutter returns such as birds and trees. For this reason, often the micro-Doppler signature of the detected target is employed as discriminative characteristic. This work aims to examine micro-Doppler jamming solutions that could be implemented on board of miniature UAV platforms in order to deploy electronic countermeasures to radar sensors, with the aim to provide useful information to the radar community to counter these

Fractional Cosine Transform (FrCT)-Turbo based OFDM for underwater acoustic communication

In this paper, a hybrid Discrete Fractional Cosine Transform (DFrCT) with Tikhonov regularization based Turbo Minimum mean square error (MMSE) equalization (DFrCT-Turbo) is presented to suppress inter-carrier interference (ICI) over underwater acoustic channels (UWA). The scheme is based on Orthogonal Frequency Division Multiplex (OFDM) scenario. In addition, an optimal order selecting method for DFrCT is developed by maximizing carrier to interference ratio (CIR) to UWA channel character. Simulation results show that BER improvement of up to 5dBs over traditional orthogonal based methods with moderate complexity

Fractional fourier based sparse channel estimation for multicarrier underwater acoustic communication system

This paper presents a hybrid sparse channel estimation based on Fractional Fourier Transform (FrFT) for orthogonal frequency division multiplex (OFDM) scenario to exploit channel sparsity of underwater acoustic (UWA) channel. A novel channel dictionary matrix based on chirp signals is constructed and mutual coherence is adopted to evaluate its preservation of sparse information. In addition, Compressive Sampling Matching Pursuit (CoSaMP) is implemented to estimate the sparse channel coefficients. Simulation results demonstrate a significant Normalized Mean Square Error (NMSE) improvement of 10dB over Basis Expansion Model (BEM) with less complexity

Measurements of surface river Doppler velocities with along-track InSAR using a single antenna

Nowadays, a worldwide database containing the historical and reliable data concerning the water surface speed of rivers is not available and would be highly desirable. In order to meet this requirement, the present work is aimed at the design of an estimation procedure for water flow velocity by means of synthetic aperture radar (SAR) data. The main technical aspect of the proposed procedure is that an along-track geometry is synthesized using a single antenna and a single image. This is achieved by exploiting a multichromatic analysis in the Doppler domain. The application of this approach allows us to obtain along-track interferometry equivalent virtual baselines much lower than the equivalent baseline corresponding to the decorrelation time of raw data preserving data coherence. The performance analysis, conducted on live airborne full-polarimetric SAR data, highlights the effectiveness of the proposed approach in providing reliable river surface velocity estimates without the need of multiple passes on the observed scene

A multi-family GLRT-based algorithm for oil spill detection

This paper deals with detection of oil spills from multi-polarization SAR images. The problem is cast in terms of a composite hypothesis test aimed at discriminating between the Polarimetric Covariance Matrix (PCM) equality (absence of oil spills in the tested region) and the situation where the region under test exhibits a PCM with at least an ordered eigenvalue smaller than that of a reference covariance. This last setup reflects the physical condition where the back scattering associated with the oil spills leads to a signal, in some eigen-directions, weaker than the one gathered from a reference area where it is a-priori known the absence of any oil slicks. A Multi-family Generalized Likelihood Ratio Test (MGLRT) approach is pursued to come up with an adaptive detector ensuring the Constant Alarm False Rate (CFAR) property. At the analysis stage, the behavior of the new architecture is investigated in comparison with a benchmark (but non-implementable) structure and some other sub-optimum adaptive detectors available in open literature. The study, conducted in the presence of both simulated and real data, confirms the practical effectiveness of the new approach

Multi-aspect micro-Doppler signatures for attitude-independent L/N quotient estimation and its application to helicopter classification

Micro-Doppler signals returned from the main rotor of a helicopter can be used for feature extraction and helicopter classification. An intrinsic feature of a helicopter that may be extracted from the micro-Doppler signatures is the L/N quotient, where N denotes the number of rotor blades and L is the blade length. However, in monostatic radar, the L/N quotient cannot be accurately estimated due to the unknown attitude angles of non-cooperative helicopters. To solve this problem, an attitude-independent L/N quotient estimation method based on multi-aspect micro-Doppler signatures is proposed in this study. The helicopter is observed from different aspect angles, and the multi-aspect micro-Doppler signatures are jointly processed to solve the attitude angles of the helicopter and estimate the L/N quotient unambiguously. Experiments with both simulated and real data demonstrate that, the proposed method is robust with respect to the attitude of the helicopter and, therefore, significantly improves the accuracy of L/N quotient estimation compared with only using the signature observed from single-aspect angle. This implies that the proposed method has the potential to increase the success rate of helicopter classification