Signal processing techniques for landmine detection using impulseground penetrating radar

Landmines are affecting the lives and livelihoods of millions of people around the world. A number of detection techniques, developed for use with impulse ground penetrating radar, are described, with emphasis on a Kalman filter based approach. Comparison of results from real data show that the Kalman filter algorithm provides the best detection performance, although its computational burden is also the highest     

Robustification of noise radar detection

A study of robust detection scheme for continuous wave noise radars is presented. The probability density function (PDF) of the noise at the input of the radar is not usually Gaussian and has heavy tails generated by impulse interferences. Although the PDF of interferences at the output of the noise radar correlator is Gaussian, impulse interferences increase the processing floor, and thus decrease the overall radar sensitivity. The proposed robustification applied to the correlator?s input signal increases the radar sensitivity in the presence of impulse interferences, and does not introduce any significant losses if the input noise is purely Gaussian.     

Multi-range-resolution radar using inverse filters

The resolution of a radar range is generally fixed regardless of the detection range. The proposed receiving system for radars is configured with multiple inverse filters so that it has different range resolutions depending on the detection range, and the signal is compressed to a narrow arbitrary pulse width of less than or equal to the reciprocal of the spectrum bandwidth of the transmitted signal. Then the proposed receiving system may be able to have no sidelobes. The frequency response function of each inverse filter used in the receiver is expressed as D( f )/S( f ), where D( f ) is the Fourier transform of the desired output waveform d(t) and S( f ) is the Fourier transform of the transmitted waveform s(t). Specific signal examples are used to clarify what sort of D( f ) and S( f ) are suitable for preventing D( f )/S( f ) from diverging. With regard to this proposed receiving system, a theoretical improvement factor is indicated for the signal-to-noise ratio, and simulations and experiments are conducted to confirm the validity of the proposed receiving system.     

三脉冲激光雷达的目标检测

讨论了如何利用数字信号处理技术提高激光雷达的目标探测能力。采用三脉冲累加技术提高信噪比1．732倍。根据三脉冲激光雷达回波信号的特点,对信号进行差分滤波和匹配滤波处理,信噪比提高约1．5倍;根据目标的相关性采用多帧相关检测对目标进行检测,通过多次的匹配,检测概率增加,虚警概率降低。外场实验结果表明,三脉冲数字激光雷达的成力大大提高,最小可检测信噪比为1．5,迎头截获距离可提高约2-3倍。     

Reliability of signal processing technique for pavement damages detection and classification using ground penetrating radar

Ground penetrating radar (GPR) signal processing is a nondestructive technique, currently performed by many agencies involved in road management and particularly promising for soil characteristics interpretation. The focus of this paper is to assess the reliability of an optimal signal processing algorithm for pavement inspection. Preliminary detection and subsequent classification of pavement damages, based on an automatic GPR analysis, have been performed and experimentally validated. A threshold analysis of the error is carried out to detect possible damages and check if they can be predicted, while a second threshold analysis determines the nature of the damage. An optimum detection procedure is performed. It implements the classical Neyman-Pearson radar test. All the settings needed by the procedure have been estimated from training sets of experimental measures. The overall performance has been evaluated by looking at the usual receiver's operating characteristic. The results show that a reasonable performance has been achieved by exploiting the spatial correlation properties of the received signal, obtained from an appropriate analysis of GPR images. The proposed system shows that automatic evaluation of subgrade soil characteristics by GPR-based signal analysis and processing can be considered reliable in a number of experimental cases.     

Automatic target recognition using multi-diversity radar

The information content of radar target signatures is a key aspect for automatic target recognition. The role of high-range resolution is investigated as a function of the illuminating wavelength. The classification performance is evaluated using (i) full-scale 2D inverse synthetic aperture radar images obtained from a stepped-frequency chirp modulation radar system and (ii) the corresponding sub-spectra of the target reflectivity function forming lower resolution images at differing centre frequencies. The classification performance as given by different combinations of RF frequencies are also evaluated and compared with the coherent reconstruction from the full bandwidth. Finally, the classification results are also computed using multiple aspects to sense the target. In this way, classification performance as function of diversity space is examined.     

Non-coherent radar CFAR detection based on goodness-of-fit tests

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 and also when several interfering targets exist, the proposed detector outperforms the conventional CFAR detector based on binary integration. Performance is also tested processing real sea clutter data collected by a non-coherent navigation radar     

Radial basis function neural network for pulse radar detection

A new approach using a radial basis function network (RBFN) for pulse compression is proposed. In the study, networks using 13-element Barker code, 35-element Barker code and 21-bit optimal sequences have been implemented. In training these networks, the RBFN-based learning algorithm was used. Simulation results show that RBFN approach has significant improvement in error convergence speed (very low training error), superior signal-to-sidelobe ratios, good noise rejection performance, improved misalignment performance, good range resolution ability and improved Doppler shift performance compared to other neural network approaches such as back-propagation, extended Kalman filter and autocorrelation function based learning algorithms. The proposed neural network approach provides a robust mean for pulse radar tracking     

Measurements of radar wave speeds in polar glaciers using a down-hole radar target technique

A new technique for measuring the speed of radar waves in polar ice sheets was developed to investigate a previously reported disagreement between the permittivities of laboratory and glacier ice. The technique involves lowering a cylindrical radar target to several carefully measured depths in a borehole and measuring the travel time of a radar wave transmitted from a surface radar unit to the target in the borehole. The experiment was performed at Dome C, East Antarctica, and Dye-3, Greenland, and useable data were collected for target depths between 200 and 800 m. After computing the range to the target along a straight ray path and after correcting the travel time for delays in the radar receiver, the velocities determined from these experiments were found to be in good agreement with the velocities predicted by Robin's empirical formula. The apparent discrepancy between the permittivity of glacier ice, as measured using the radar wide-angle reflection method, and laboratory ice now seems to be due in large part to signal delay in the radar receiver that was ignored in earlier experiments.     

倒车雷达探测范围测量方法及准确度分析

提出一种测量倒车雷达探测范围的方法,利用激光器、激光测距仪及三坐标测量机结合超声波雷达的原理,通过光滑拟合雷达最远探测点的方式,可视化显示倒车雷达探测范围,经过试验验证该方法的测量准确度为2%,最后利用该方法确定倒车雷达在视野盲区内为不同障碍物提供的有效探测范围。该文通过将整车上的倒车雷达复制到台架上的方式测量倒车雷达的探测范围,为国内尚不明确的倒车雷达测量范围测试标准提供参考。     

Radar cross section measurements using near-field radar imaging

In this paper a technique to obtain the far-field scattering signature of bodies, using near-field measurements, is proposed. The method is based on near-field radar imaging techniques. The backscattered field data are collected in a controlled environment over a large frequency band and aspect angle using a near-field antenna. A focused radar image of the body is generated. Probe correction to compensate for the radiation pattern of the interrogating antenna is conducted during the two-dimensional imaging of the object. The contribution from each scattering center to the total backscattered far-field is obtained from the radar image. The proposed technique is applied to obtain the far-field radar cross section (RCS) for an object from near-field measurements conducted in an anechoic chamber at the University of Pretoria, South Africa     

Buried ordnance detection: electromagnetic modeling of munition-mounted radio frequency identification tags

In order to improve means for locating unexploded ordnance items (UXO) and significantly discriminating UXO from clutter, it is desired to tag ordnance items before they are delivered. The munition tagging envisioned will make use of current passive radio frequency identification (RFID) tag technology. The tags will provide information on the munition's location and identity when the UXO tag interrogation module is brought nearby. Knowledge of the magnetic field's behavior is essential in understanding the designs required to transmit energy from the above-ground interrogator to the tag and from the tag back to the above-ground receiver. The munition, being a large metal structure in such close proximity to the tags, will affect their operation because of electromagnetic boundary conditions and the tags' specific circuitry. To this end, modeling of the magnetic fields was required. This paper presents the results of this modeling effort and includes experimental findings. The modeling efforts demonstrated that detection depths to 1 m would be achievable, provided the system is magnetically optimized.     

Effect of moisture on the reliability of void detection in brickwork masonry using radar, ultrasonic and complex resistivity tomography

The influence of moisture on the reliability of detection of larger voids in brickwork masonry was investigated using three non-destructive techniques: radar, ultrasonic and complex resistivity (CR). Radar and ultrasonic travel time tomography, as well as CR tomography, were performed over a specific cross section of a specimen containing a large void at a known position to determine the influence of different levels of moisture content in the brickwork on the wave velocities and the CR magnitude. We defined a numerical estimator to quantitatively determine the void detection efficiency from the images obtained when exposing the specimen to moisture. The results showed radar to be the most reliable technique for void detection in both dry and wet masonry, while CR performed much better in detecting larger air voids in wet masonry.     

Classification of primary radar tracks using gaussian mixture models

Classification of primary surveillance radar tracks as either aircraft or non-aircraft is critical to a number of emerging applications, including airspace situational awareness and collision avoidance. Substantial research has focused on target classification of pre-processed radar surveillance data. Unfortunately, many non-aircraft tracks still pass through the clutter-reduction processing built into the aviation surveillance radars used by the Federal Aviation Administration. This paper demonstrates an approach to radar track classification that uses only post-processed position reports and does not require features that are typically only available during the pre-processing stage. Gaussian mixture models learned from recorded data are shown to perform well without the use of features that have been traditionally used for target classification, such as radar crosssection measurements.     

Adaptive radar detection in the presence of mutual coupling and near-field effects

The problem of adaptive radar detection in the presence of near-field and mutual coupling effects - two phenomena which may significantly affect the radar performance - is considered. To this end, the generalised likelihood ratio test criterion is used (both one-step and two-step) and adaptive decision rules capable of operating in realistic scenarios are devised, where the far-field hypothesis can be no longer met and the mutual coupling is present. At the analysis stage, the performance of the proposed detectors is evaluated through Montecarlo simulations. The results show that appreciable performance improvements can be obtained if near-field and mutual coupling effects are properly accounted for at the design stage.     

Azimuth-invariant bistatic multichannel synthetic aperture radar for moving target detection and location

Ground moving target indication (GMTI) is one of the most important applications of the bistatic synthetic aperture radar (SAR) system as well as the monostatic system. An algorithm for moving target detection and location is presented with an azimuth-invariant bistatic multichannel SAR, which consists of one transmitter (channel) and multireceivers (multichannel). The algorithm is based on the discussion of the particularities of the bistatic SAR configuration including coherence improvement and clutter characteristics. Then, the corresponding compensating methods including two-dimensional range-azimuth prefiltering and bistatic differential range correction are proposed to solve these particularities. It is shown that using the compensating methods, the stationary clutter can be suppressed and the moving parameters of ground targets can be estimated accurately. Finally, simulation results demonstrate the effectiveness of the proposed algorithm.     

The efficiency analysis of container port production using DEA panel data approaches

Applications of Data Envelopment Analysis (DEA) to container port production have been largely restricted to standard DEA models using cross-sectional data. The efficiency results derived may be biased; for instance, as the result of random effects or a recent investment in future production. In overcoming this problem, panel data on container port production may be more suitable for medium- to long-term efficiency analysis. This paper evaluates available DEA panel data approaches by applying them to a sample of 25 leading container ports. Empirical results validate the necessity of utilizing panel data and reveal that considerable waste exists in container port production. It also provides a basis for assessing the competitiveness of container ports, for benchmarking best practice and identifying specific sources or causes of inefficiency.     

Remote monitoring of the earthquake cycle using satellite radar interferometry

The earthquake cycle is poorly understood. Earthquakes continue to occur on previously unrecognized faults. Earthquake prediction seems impossible. These remain the facts despite nearly 100 years of intensive study since the earthquake cycle was first conceptualized. Using data acquired from satellites in orbit 800 km above the Earth, a new technique, radar interferometry (InSAR), has the potential to solve these problems. For the first time, detailed maps of the warping of the Earth's surface during the earthquake cycle can be obtained with a spatial resolution of a few tens of metres and a precision of a few millimetres. InSAR does not need equipment on the ground or expensive field campaigns, so it can gather crucial data on earthquakes and the seismic cycle from some of the remotest areas of the planet. In this article, I review some of the remarkable observations of the earthquake cycle already made using radar interferometry and speculate on breakthroughs that are tantalizingly close.     

Photon-number-resolving detection using time-multiplexing

Abstract

Detectors that can resolve photon number are needed in many quantum information technologies. In order to be useful in quantum information processing, such detectors should be simple, easy to use, and be scalable to resolve any number of photons, as the application may require great portability such as in quantum cryptography. Here we describe the construction of a time-multiplexed detector, which uses a pair of standard avalanche photodiodes operated in Geiger mode. The detection technique is analysed theoretically and tested experimentally using a pulsed source of weak coherent light.