Sharif Digital Repository

CFAR detector is an essential component in any radar system. This component ensures that the system may not be overloaded by false targets. In the past it was common to model the interfering signal (clutter) in a radar system with a Rayleigh distribution. But as a progress in the radar systems, nowadays the Rayleigh model is insufficient, therefore some other models such as Weibull and lognormal are proposed and CFAR detectors for these models are developed through the papers. But majority of these proposed CFAR detectors are derived for single pulse operation. When more than one pulse exists, it is proposed to use binary integrator to improve the performance. It is mentioned through... 

The present study aims to evaluate the important issue of elimination of direct path interference and clutter in ambiguity function and detection of passive radars with adaptive filters. The efficiency and performance of each of them were investigated. Finally, by simulation and their learning curve, the best algorithm was proposed for these radars  

Order statistic (OS) CFAR processor is a powerful detector, but similar to many other CFAR detectors, suffers from clutter edge as well as interfering targets. To overcome these problems, two derivations of this detector have been developed. These are order statistic greatest of (OSGO) and order statistic smallest of (OSSO) CFAR processors. The cost, paid for this improvement, is a considerable decrease in detection probability for homogenous Weibull clutter. Furthermore, a substantial performance degradation of OSGO in interfering target (high target masking effect) and an excessive false alarm of OSSO in clutter edge, also, occur. This behavior is a result of non-soft rules used in these... 

In Distributed detection systems, restricting the output of the local decision to one bit certainly implies a substantial information loss. In this paper, we consider the fuzzy detection, which uses a function called membership function for mapping the observation space of each local detector to a value between 0 and 1, indicating the degree of assurance about presence or absence of a signal. In this case, we examine the problem of distributed Maximum Likelihood (ML) and Order Statistic (OS) constant false alarm rate (CFAR) detections using fuzzy fusion rules such as "Algebraic Product"(AP), "Algebraic Sum"(AS), "Union"(Un) and " Intersection"(IS) in the fusion centre. For the Weibull... 

Using the Fractal Geometry in Signal processing has been extended nowadays [1]. They have found several applications in signal detection and recognitions. They use the chaotic feature of the noise and clutter and try to distinguish between the noise, clutter and the desired target [2] [3]. Recent works show that lots of clutters like sea and ground clutters have fractal behavior so this kind of approach to the signal detection has been extended these days[3][4]. In this paper we have used the Box-Counts of a signal rather than the Fractal dimension of a signal as will be defined later in the text. By applying the new defined concept we have developed different methods of signal detection. We... 

The relative velocity between ground surface and receiver platform leads to clutter expansion in the range-doppler surface. The expanded clutters can mask slow moving targets. The passive radar is a low cost and light weight radar with high detection ability, due to its multistatic geometry. In this paper, we employ the MISO passive radar with at least four transmitters of opportunity to constitute an over-determined system of equations. We propose an algorithm to localize moving targets in the presence of clutters. In the first step, the clutters are separated from moving targets and in the second one, the position and velocity of the target are computed by solving the system of equations.... 

For the target parameter estimation in MIMO radars in the presence of strong clutter, non-adaptive compressive sensing methods have a poor performance. On the other hand, the adaptive ones usually need higher data acquisition time. In this paper, we propose an adaptive compressive sensing method called L-BGT that has tolerable data acquisition time. furthermore, we have presented the essential changes in a distributed MIMO radar to exploit an adaptive group testing compressive sensing method  

Passive radars use illuminators of opportunity to detect target and measure its parameters. The usual processing routine consists of direct path interference and clutter removal and computation of cross ambiguity function (CAF) to estimate ampIitude-range-Doppler surface. Main parameters affecting this procedure are direct path interference and clutter, receiver thermal noise and near large targets. This paper presents an investigation on effect of each parameter and tries to estimate processing gain of each Block. A comparison between different adaptive interference removal methods also presented  

A robust method for ultra-wideband (UWB) imaging of buried shallow objects based on time gating, Wiener filtering, as well as constant false alarm rate (CFAR) is proposed. Moreover, it is demonstrated that Wiener filtering can be used as a clutter removal tool in UWB signal applications. Basically, the problem with time gating method is that the length of the timing window for unknown targets cannot be determined accurately in advance. In fact, it is a blind methodology and some targets can be missed due to a lack of pre-knowledge about their depth. Imprecise window length selection leads to missing some parts of the target signals along with the clutter, which in turn increases the missed... 

This study presents and analyses a novel joint detection and parameters estimation of multiple targets using a co-located multiple input/multiple output radar with moving platform, in the presence of clutter and background noise. A notable feature of the proposed approach is that clutter cancellation is independent of received data. Moreover, to decrease the computational load, the authors propose to perform the target detection and parameters estimation by directly processing on the compressive measurements as opposed to Nyquist samples. © The Institution of Engineering and Technology  

While visual target tracking is one of the noteworthy and the most active research areas in computer vision and machine learning, many challenges are still unresolved. In this paper, an adaptive generic target tracker is proposed that includes the adaptive determination of learning parameters from spatio-temporal context model, analysis of prior targets and confidence map for accurate target localization, and modified scale estimation scheme based on confidence map. According to spatio-temporal context model, the learning parameters are adaptively determined for achieving confidence map and target scale robustly. Moreover, analysis of the confidence map helps our tracker to change context... 

In this paper the structure of Maximum Likelihood (ML) CFAR for lognormal clutter is derived assuming that some reference samples are censored to avoid destructive effect of interfering targets. It is shown that under some acceptable approximations we will achieve in a simple structure for this detector which is suitable for real time processing. The proposed detector is compared with non censored ML CFAR (i.e. logt CFAR) via simulation. It is shown that while the proposed detector is a little weaker than logt CFAR in homogeneous clutter, in non homogeneous clutter it outperforms the logt CFAR  

This paper considers the problem of constant false alarm rate (CFAR) detection of radar targets using multiple observations. In the Gaussian clutter scenario, the structure of the optimum (uniformly most powerful) CFAR detector is rather simple, but when the clutter is heavy-tailed, that is non-Gaussian distributed, the derivation of the optimal detector becomes infeasible. For this latter relevant case, a new CFAR algorithm is porposed based on goodness-of-fit (GoF) tests. The performance of the proposed detector is numerically investigated through Monte Carlo simulations assuming heavy-tailed Weibull and Lognormal distributed clutter. Numerical results shown that, in heavy-tailed clutter... 

Multiple target detection in conventional PCL (Passive Coherent Location) radar systems by means of Ambiguity Function Processing and without any powerful algorithm is impossible. Presented Gradual Clean Algorithm (GCA) is a new and simple method, which could provide the perfect detection in noisy environment and heavy clutter condition up to SNR=-15 dB and SCR=-100 dB (clutter is assumed as a distributed target with large RCS). Determining the number of real targets and keeping the false alarm probability approximately constant are the presented algorithm capabilities  

In this paper a novel algorithm for detection, parameter estimation, and image formation of a moving target in ground-based circular strip-map synthetic aperture radar (GBCSAR) is proposed. Because multiple similar scans of the scene with short revisit time are possible, moving target detection is performed by clutter cancellation. Despite of the frequency-domain or multi-antenna clutter cancellation methods, this system has the capability of removing the clutter completely regardless of the target speed or the signal to clutter ratio (SCR). Estimation of target parameters and range-cell migration correction (RCMC) is based on comparing two consecutive target images. Finally the azimuth... 

Sea clutter refers to the radar returns from the sea surface. Accurate modelling of sea clutter and detection of low observable targets within sea clutter are major problems in remote sensing and radar signal processing applications. Recently fractal geometry is applied to the analysis of high range resolution radar sea clutters. The box-counting method is widely used to estimate fractal dimension but it has some drawbacks rarely considered in literature. We explain the problem of box size range and present a novel method to select an appropriate range  

Waveform design for target identification and classification in MIMO radar systems has been studied in several recent works. While the previous works assumed that the noise was independent of the transmission signals, here we extend the results to the signal dependent noise (clutter). We consider two scenarios. In the first scenario it is assumed that different transmit antennas see uncorrelated aspects of the target. In the second scenario, we consider the correlated target. As clutter is dependent to signal, target estimation error cannot vanish only by increasing the transmission power. It can be shown that in the second scenario, MIMO radar receiver can nullify the clutter subspace.... 

Design of a vision-based target tracking control strategy for a dual-rotor UAV with tilting rotors is presented. In this research, the under-study UAV is equipped with a sliding mass that can slide over a motorized linear track attached to the UAV's fuselage enabling it to perform sophisticated maneuvers by monitoring its five controllable degrees of freedom. The dynamic model of the system is first derived and then a model-based controller using vision based pose estimation, obtained via an onboard down-looking camera, is designed enabling the UAV to: (1) pitch hover in position, (2) servo towards a target position, and (3) track a moving target. Simulations show the premise of the proposed... 

It is shown that the detection performance can be significantly improved using the recent technology of multiple-input multiple-output (MIMO) radar systems. This is a result of the spatial diversity in such systems due to the viewing of the target from different angles. On the other hand, the moving target indication (MTI) processing has long been known and applied in the traditional pulse radars to detect weak moving targets in the presence of strong clutter signals. The authors propose a procedure based on the compressive sensing idea, in order to apply the MTI processing in a MIMO radar with widely separated antennas. Although a clutter is included in the signal model and a different... 

As radar signals propagate above the ocean surface to determine the trajectory of a target, the signals that are reflected directly from the target arrive at the receiver along with indirect signals reflected from the ocean surface. These unwanted signals must be properly filtered; otherwise, their interference may mislead the signal receiver and significantly degrade the tracking performance of the radar. To this end, we propose a low-elevation target tracking mechanism considering the specular and diffuse reflection effects of multipath propagation over the ocean surface simultaneously. The proposed mechanism consists of a state-space model and a particle filtering algorithm and promises...