Showing papers in "Iet Radar Sonar and Navigation in 2009"

Waveform design in signal-dependent interference and application to target recognition with multiple transmissions

Abstract: The authors present illumination waveforms matched to stochastic targets in the presence of signal-dependent interference. The waveforms are formed by SNR and mutual information (MI) optimisation. We also use these waveforms in cognitive radar (CR) target identification application. In this application, the radar system attempts to identify a deterministic or random target using multiple transmissions. These transmissions are adaptively modified in response to previously received echoes. In addition, the authors present a new multi-band application of the CR platform.

New ISAR imaging algorithm based on modified Wigner–Ville distribution

Abstract: Inverse synthetic aperture radar (ISAR) imaging of air, space or ship targets with complex motion has attracted the attention of many researchers in the past decade. Complex motion of targets induce cross-range scatterer-variant quadratic phase terms, which will degrade the cross-range resolution and affect focusing quality. A new algorithm is proposed for the ISAR imaging of complex moving targets. First, conventional range alignment, phase compensation and range compression are performed over the raw phase history data such that each range bin can be modelled as the sum of several linear frequency modulation or chirp signals. Secondly, a modified-Wigner-Ville distribution (referred to as M-WVD) approach is proposed, which is based on a scale transform in the time-frequency distribution plane and can effectively suppress the troublesome cross-term interference associated with WVD via coherent integration. Finally, the azimuth ISAR image can be obtained via a simple maximisation projection from the two-dimensional accumulated plot to the azimuth dimension. Compared with existing WVD-based ISAR imaging algorithms, the proposed method has the following features: better cross-term interference reduction achieved at no resolution loss, computationally more efficient with no expensive two-dimensional parameter search, and higher signal processing gain because of coherent integration during the whole imaging time. Both numerical and experimental results are provided to demonstrate the performance of the proposed method.

Space-time constant modulus algorithm for multipath removal on the reference signal exploited by passive bistatic radar

Abstract: The authors address the problem of multipath cancellation in the reference signal used in passive bistatic radar (PBR), which exploits an existing transmitter as emitter of opportunity. The presence of multipath echoes in the reference signal is demonstrated to strongly affect the detection performance of passive radar. Based on the well-known constant modulus algorithm (CMA) approach in the time-domain, new multi-dimensional techniques are considered for the adaptive equalisation of the reference signal based on an array of antennas and multiple receiving channels. The effectiveness of these techniques for PBR purposes is demonstrated with reference to typical simulated scenarios. The considered strategies, addressed as space-CMA and space-time-CMA, are shown to be able to recover the performance loss because of the multipath contribution in the reference signal so that they appear as very appealing solutions for PBR equipped with an array of antennas and multiple receiving channels.

Adaptive beamforming for high-frequency over-the-horizon passive radar

Abstract: Target detection and tracking systems using emitters of opportunity have received significant interest recently, especially those which exploit VHF and UHF broadcasts as signal sources in so-called passive radar systems. Here, the authors discuss an experimental system in the high-frequency (HF) band, where due to long-distance ionospheric propagation of radio waves in the 3-30-MHz spectrum, the illuminator may be located well beyond the line-of-sight. In this study, live data was recorded by a high dynamic range multi-channel digital receiver connected to a two-dimensional (L-shaped) antenna array, and signals from an uncooperative HF over-the-horizon (OTH) radar transmitter have been captured and analysed. As a preliminary step towards the development of a general HF-OTH passive radar system, the scope of this work is to compare the performance of conventional and adaptive spatial processing techniques in terms of their ability to cancel direct-wave interference and protect useful signal echoes to detect a small cooperative aircraft target. In particular, an alternative adaptive beamforming method specifically tailored to this application is proposed, and its practical performance is compared with classical and standard adaptive beamforming approaches. GPS data measured on-board the cooperative aircraft provided accurate ground truth of the flight path, enabling target profiles in bi-static range, Doppler frequency and direction-of-arrival (azimuth/elevation) to be calculated as a function of time. This information permitted the different processing schemes to be evaluated with a high degree of confidence. The experimental system and live data analysed are exclusively from the HF Radar program of the Defence Science and Technology Organisation (DSTO), Australia.

Modified input estimation technique for tracking manoeuvring targets

Abstract: A new input estimation (IE) model for problems in tracking manoeuvring targets is proposed The proposed model is constructed by combining the two models of uncertainties, Bayesian and Fisher The conventional model, which describes targets with manoeuvre, is based on the state vector of target position and velocity The acceleration is treated as an additive input term in the corresponding state equation The proposed method is a Kalman filter-based tracking scheme with the IE approach The proposed model is a special augmentation in the state-space model which considers both the state vector and the unknown input vector as a new augmented state vector In the proposed scheme, the original state and acceleration vectors are estimated simultaneously with a standard Kalman filter The proposed tracking algorithm operates in both the non-manoeuvring and the manoeuvring modes and the manoeuvre detection procedure is eliminated The theoretical development is verified by simulation results, which also contain some examples of tracking typical target manoeuvres The results are compared with a traditional IE method A comparison based on the Monte-Carlo simulation is also made to evaluate the performances of the proposed method in three scenarios: low, medium and high manoeuvring target

Target localisation techniques and tools for multiple-input multiple-output radar

Abstract: This study presents a comparative study of coherent and non-coherent target localisation techniques for multiple-input multiple-output (MIMO) radar systems with widely distributed elements. Performance is evaluated based on closed-form solutions developed for the best linear unbiased estimator (BLUE) for each of the localisation methods. These estimators afford insights into the relation between radar locations, target location and localisation accuracy. In particular, the means squared error of the BLUE is factored into a term dependent on signal and processing characteristics and a term dependent on sensor locations. The latter is referred to as geometric dilution of precision (GDOP). The best achievable accuracy for the coherent case is obtained, and a comparative study with the non-coherent case is presented. MIMO radar systems with coherent processing are shown to benefit from a gain because of coherent processing among sensors. This gain is referred to as coherent localisation gain, and it is proportional to the ratio of the signal carrier frequency to the effective bandwidth (a large ratio for typical signals). The footprint of multiple transmit/receive sensors results in a gain, referred to as MIMO gain, for both processing techniques. The MIMO gain is proportional to the product of the number of transmitting and receiving sensors. Analysis of the MIMO gain through the use of GDOP contour maps demonstrate the achievable accuracy at various target locations for a given layout of sensors.

Application of the Radon transform to detect small-targets in sea clutter

Abstract: The authors present a novel and heuristic approach for the detection of low radar cross-section targets in high-resolution sea clutter. The proposed technique is based on the application of the Radon transform to range-time matrices formed by column-wise storage of consecutive range profiles. The objective of this paper is 2-fold: to analyse the effect of the transform on real high-resolution sea clutter and to describe a detection scheme based on the insight obtained. The proposed technique emulates the behaviour of traditional motion target detection algorithms without the need for reliable Doppler information. It also constitutes a powerful non-coherent integration strategy of the target-s energy along its specific path on the range-time plot. The performance of the detection technique has been tested against real high-resolution sea clutter data, acquired at the south coast of Spain with an in-house developed continuous wave linear frequency modulated millimetre-wave radar system. Monte Carlo simulations show a significant improvement over the conventional cell averaging constant false alarm rate schemes.

Multiple-input multiple-output over-thehorizon radar: experimental results

Abstract: Results from an experiment that applied one class of multiple-input multiple-output (MIMO) waveform techniques to over-the-horizon radar (OTHR) are reported. The experiment objective was to demonstrate that adaptive transmitter beamforming could be used in an appropriately design radar to reject spatially discrete Doppler-spread clutter. In the particular MIMO radar architecture that the authors call non-causal transmit beamforming, conventional or adaptive transmitter beamforming occurs following waveform transmission, propagation, scatter from targets and clutter sources, return propagation and finally signal reception. In the case reported herein spatially discrete clutter was successfully rejected to the noise floor of the radar return with rejection in excess of 35 dB achieved using common adaptive algorithms and straightforward training data selection. As part of the rejection algorithm the transmitted waveform direction-of-departure (DOD) from the transmitter array to the target was estimated and used as the preserved steer direction in the adaptive beamformer. The DOD estimates agree well with the geometrically determined true values. The demonstration of non-causal transmit beamforming suggests that it will be possible to create multiple simultaneous adaptive range-dependent transmitter beams with an appropriately designed OTHR. This has several applications including for the mitigation of Doppler-spread clutter.

Synthesis of compromise sum-difference arrays through time-modulation

Abstract: In this paper, time-modulation is exploited for the synthesis of monopulse sub-arrayed antennas. The solution of the compromise sum-difference problem is obtained by setting the set of static excitations to an optimal sum set and synthesizing the “best compromise” difference pattern through a Continuous Partition Method (CPM) based approach. The array elements are aggregated into sub-arrays controlled by means of RF switches with optimized “on” time-durations. The switch-on instants of the pulse sequences are then computed by means of a particle swarm optimizer to reduce the interferences caused by the sideband radiations. A selected set of numerical results is reported to assess the potentialities of time-modulation in dealing with the synthesis problem at hand. This paper is a postprint of a paper submitted to and accepted for publication in Radar, Sonar & Navigation and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at IET Digital Library.

Orthogonal frequency-division multiplexing radar signal design with optimised ambiguity function and low peak-to-average power ratio

Abstract: Considering the important role of the ambiguity function (AF) of a signal regarding the performance of a matched filter bank for the detection of targets and the estimation of their ranges and velocities, the thumbtack shape is assumed to be the desirable shape of the AF and the method of least squares for the synthesis of the AF is introduced. Then, an iterative method for the allocation of a proper phase to the desired AF is proposed to obtain better results. This method is then applied to select the proper codes for the synthesis of pulsed orthogonal frequency-division multiplexing signals. It is also shown how this method can reduce sidelobes, almost uniformly, throughout the entire ambiguity plane. Finally, an efficient algorithm is presented, which modifies the produced codes in order to reach a lower peak-to-average power ratio suitable for transmission.

Theory and simulation of ionospheric effects on synthetic aperture radar

Abstract: Space-based synthetic aperture radar (SAR) necessarily involves imaging through the ionosphere. At low frequencies (VHF, UHF and L-band) the ionosphere will degrade the SAR image. Previous work has shown that the amount of image degradation strongly depends on the integrated strength of ionospheric turbulence, C k L. The focusing, sidelobes and integrated sidelobe ratio all depend on C k L in a manner that can be directly predicted by a simple analytic theory, which is reviewed and extended to cover any synthetic aperture length. Simulations of the ionosphere, using a thin phase screen parabolic equation approach, are performed under different ionospheric conditions for a number of possible SAR systems and the results compared with the analytic theory. It is concluded that, provided that the scattering is weak, the theory represents a good predictor of SAR performance, even at UHF. The known statistics of C k L can therefore be used to predict the performance of any trans-ionospheric SAR without performing a simulation.

Modelling of low-latitude ionosphere using modified planar fit method for GAGAN

Abstract: Several countries have been developing satellite-based augmentation systems (SBAS) for improving positional accuracy of global positioning system (GPS). India is also developing one such system popularly known as GPS aided geo augmented navigation (GAGAN) system. Modelling of ionospheric effects is one of the major challenges in developing precise and reliable GAGAN. The high values of total electron content (TEC), the large diurnal and seasonal variability and intense irregularities present in the low-latitude ionosphere, lead to unacceptable positional errors in GAGAN service region. Todd Walter et al. of Stanford University, USA have made significant contribution in the area of SBAS ionospheric grid modelling by developing the popularly known planar fit model. It is reported by Walter et al. (2000) that a constant decorrelation value of 35 cm was proposed over the wide area augmentation system (WAAS) service region. To provide accurate estimation of ionospheric delays at user ionospheric pierce points (IPP) during a storm or intense irregularities, an irregularity detector and a decorrelation adaptor are incorporated in the modelling. As planar fit model is not adequate to model intense irregularities of Indian ionosphere, a modified planar fit model is applied for GAGAN data on similar lines as was done for WAAS and the results are encouraging.

Joint time difference of arrival/angle of arrival position finding in passive radar

Abstract: Several target position finding methods are proposed in various papers mainly regarding sensor networks. However, the problem of position finding in passive radar systems is somewhat different from the general case of sensor networks. Generally, in a passive radar system, there are few receivers located at short distances when compared with the it distance from the target. In this case, a problem known as geometric dilution of precision (GDP) occurs, which considerably increases the error of many proposed methods. This phenomenon can even make the position finding equations non-solvable. Regarding this fact, we have developed a least mean square error (LMSE) based method, which uses both the angle of arrival (AOA) and time difference of arrival (TDOA) measurements to estimate almost precisely the position of very distant targets in a passive radar system. A simple equation is derived here to compare the TDOA and AOA accuracies. Then, it is shown that whenever the accuracies of these two measurements are comparable, the proposed method estimates the target position more precisely than the conventional AOA-only and TDOA-only methods. It also avoids the non-convergence behaviour encountered in TDOA-only methods.

Efficient direct position determination of orthogonal frequency division multiplexing signals

Abstract: The authors present an efficient method for positioning of orthogonal frequency division multiplexing (OFDM) signals. The method, called direct position determination (DPD), enables one to determine the emitter position in a single search operation. In formerly published articles on DPD, the signal was assumed to be a narrowband Gaussian source, which was subjected to a rather simple flat-fading channel model. Here, the authors extend the DPD algorithm to handle the OFDM signals that propagate through a frequency-selective channel, and derive the least squares estimator (LSE) for the problem. In addition, the authors present a method for a fine 2D position estimation, which enables one to reduce the DPD computational complexity without compromising on its estimation accuracy.

Linear and adaptive spaceborne threedimensional SAR tomography: a comparison on real data

Abstract: Three-dimensional (3-D) synthetic aperture radar (SAR) imaging is a recent technique, based on coherent SAR data combination, and aims to obtain a full 3-D analysis in space. It is a multibaseline extension of the SAR interferometry concept and offers new options for the analysis and monitoring of ground scenes by means of the capability of separating the scattering phenomena along the height dimension. In this work, the authors summarise and extend the results obtained by processing real ERS satellite urban data characterised by a long time span of acquisition and non-uniformly spaced satellite passes, comparing the performance in height focusing obtained with a singular value decomposition (SVD)-based method and adaptive beamforming.

Foundation for mitigating range dependence in radar space-time adaptive processing

Abstract: The problem of detecting slow-moving targets using a space-time adaptive processing (STAP) radar is addressed. The determination of the optimum interference-rejection weights at each range is based on snapshots at neighbouring ranges. However, in virtually all bistatic configurations or/and when using conformal antenna arrays (CAA), snapshot statistics are range dependent, which results in poor detection performance. To address this issue, a foundation for range-dependence compensation in STAP in the case of Gaussian interference and noise is proposed. The realistic case where received snapshots are the only source of information for mitigating the range dependence is considered. To illustrate the usefulness of the proposed foundation, this foundation is used to design a method to adaptively compensate for range dependence in a challenging situation, that is, for a radar using a CAA and operating in a bistatic configuration.

Radar target classification method with reduced aspect dependency and improved noise performance using multiple signal classification algorithm

Abstract: This study introduces a novel aspect and polarisation invariant radar target classification method based on the use of multiple signal classification (MUSIC) algorithm for feature extraction. In the suggested method, for each candidate target at each designated reference aspect, feature matrices called ‘MUSIC spectrum matrices (MSMs)’ are constructed using the target's scattered data at different late-time intervals. An individual MSM corresponds to a map of a target's natural resonance-related power distribution over the complex frequency plane under the chosen aspect angle/late-time interval conditions. The collection of these feature matrices is used first to determine the best late-time interval for optimal feature extraction. Then, the MSM of a target, which are computed over the optimal time interval at all reference aspects, are superposed to obtain the ‘fused MUSIC spectrum matrix (FMSM)’. The FMSM of a target is its main classifier feature in the proposed method as the aspect dependency of an FMSM is highly reduced because of its multi-aspect construction process. The suggested method is demonstrated for both simple and complex target geometries such as conducting spheres, dielectric spheres and small-scale aircraft targets with high accuracy rates even for low SNR values using feature fusion at only a few different reference aspects.

Performance of the adaptive generalised matched subspace constant false alarm rate detector in non-Gaussian noise: an experimental analysis

Abstract: The authors deal with the performance analysis of an adaptive version of the generalised matched subspace detector (GMSD) in compound-Gaussian clutter with unknown covariance matrix. The original GMSD was proposed to detect subspace signals in compound-Gaussian noise with known covariance matrix and ensures the constant false alarm rate (CFAR) property. In real situations, this assumption is unrealistic, which means that the covariance matrix must be estimated from training data. The authors use a robust estimate of the covariance matrix called the fixed-point estimate, recently proposed in the literature. The performance of the obtained adaptive detector, in terms of CFAR behaviour and probability of detection, is evaluated in the presence of real sea clutter data, collected by the McMaster IPIX radar.

Reduced-rank space-time adaptive processing using a modified projection approximation subspace tracking deflation approach

Abstract: The projection approximation subspace tracking deflation (PASTd) algorithm is investigated in the context of the reduced-rank space-time adaptive processing (RR-STAP), where a recursive approach is employed to estimate the clutter subspace. Instead of a direct use of the classic PASTd algorithm in the RR-STAP, which suffers from a slow convergence rate because of the sequential tracking of multiple clutter eigenvectors, a modified PASTd adapted to the STAP is presented. In comparison with the conventional eigenvalue decomposition approach, the presented algorithm is computationally much more efficient and is also able to achieve comparable convergence effectiveness. The presented methodology is validated by the Monte Carlo simulation.

Excitation matching procedure for sub-arrayed monopulse arrays with maximum directivity

Abstract: In this paper, the maximization of the directivity of compromise difference patterns in subarrayed monopulse linear array antennas with optimum sum mode is addressed by means of a two-stage excitation matching procedure. The knowledge of the independently optimum difference excitations, which provide the maximum directivity, is exploited with an efficient matching technique based on the contiguous partition method. Simple and reliable compromise solutions, characterized by a reduced complexity as well as easier antenna manufacturing, are synthesized to assess the effectiveness of the proposed method also in comparison with state-of-the-art methods devoted to the directivity maximization. This paper is a postprint of a paper submitted to and accepted for publication in Radar, Sonar & Navigation and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at IET Digital Library.

Ionospheric clutter mitigation using one-dimensional or two-dimensional wavelet processing

Abstract: Ionospheric clutter mitigation is an important issue for high-frequency surface wave radar (HFSWR) signal processing. Clutter results from a sky wave propagation mode, which is backscattered by ionospheric ionisation irregularities. The random behaviour and the high strength of clutter signals can strongly limit the HFSWR detection capabilities. Here, an ionospheric clutter mitigation processing using wavelets is described. This new approach is founded on the ability of wavelets to separate signals having different variation scales or different directions of variations. The results obtained on real clutter signals with simulated targets are reported. Using the proposed method, one can expect, at mid-latitude, an improvement of the target-to-clutter ratio of 20-30-dB.

ISAR imaging of manoeuvring targets with the range instantaneous chirp rate technique

Abstract: The conventional range instantaneous Doppler (RID) algorithm is a well accepted inverse synthetic aperture radar (ISAR) imaging method for manoeuvring targets. In the RID imaging, the cross-range resolution depends on the instantaneous Doppler of scatterers at the imaging instant. For a high manoeuvring target, the instantaneous Doppler of scatterers may be small at some imaging instants and the satisfactory RID images may not be obtained. On the other hand, a large instantaneous chirp rate is often present for the same scatterer at the same instant for RID imaging. In order to obtain some additional information of a manoeuvring target, a novel ISAR imaging approach, referred to as the range instantaneous chirp (RIC), is proposed based on instantaneous chirp rate of scatterer to provide cross-range resolution. Using the proposed imaging algorithm, with the same received data of RID, a RIC image is generated at the same instant with a different ‘view’. Therefore the RIC image may provide some additional information that is not shown in the RID image. With both the RIC and RID images, a better target recognition and identification can be achieved for high-manoeuvring targets. The proposed RIC algorithm is verified by raw radar data.

Signal-to-noise ratio threshold effect in track before detect

Abstract: Track before detect (TBD) refers to simultaneous detection and tracking using unthresholded sensor responses over time. The motivation for TBD is its capacity to deal with low signal-to-noise ratio (SNR) targets. Previously, the achievable error for TBD has been established using Cramer–Rao analysis. Although computationally simple the Cramer–Rao bound is not useful at low SNR as it does not predict the threshold effect. A more accurate notion of the achievable performance at low SNRs is provided by the computationally more complicated Barankin bound. The computational complexity of the Barankin bound arises from the need to optimise over a number of test points, with the tightness of bound increasing with the number of test points. An approximation to the Barankin bound is proposed which permits the use of multiple test points with reasonable computational expense. The improvements in threshold SNR prediction offered by the proposed bound are demonstrated in numerical examples.

Novel joint time delay and frequency estimation method

Abstract: A novel algorithm has been proposed for joint time delay and frequency estimation of sinusoidal signals received at multiple separated sensors. The joint time delay and frequency estimation problem is linked to a trilinear model. Exploiting this link, it derives a trilinear decomposition-based joint time delay and frequency method algorithm. The simulation results reveal that the algorithm performance is close to that of the Cramer-Rao lower bound, and the proposed algorithm even supports small sample sizes.

Adaptive ground clutter suppression for conformal array radar systems

Abstract: Conformal arrays (CFAs) possess certain desirable characteristics for deployment on unmanned aerial vehicles and other payload-limited platforms. However, the CFA non-planar geometry induces clutter non-stationarity, resulting in elevated signal-to-interference-plus-noise ratio (SINR) loss when applying conventional space-time adaptive processing (STAP) algorithms. Non-stationary clutter leads to covariance matrix estimation error and, consequently, an erroneous STAP frequency response. In this study, the authors examine two practical conformal antenna configurations: a belly-mounted canoe and a nose-mounted, chined shape. Using high-fidelity signal models, the authors show traditional STAP losses in excess of 10-dB because of the effects of clutter non-stationarity. The authors then investigate a number of ameliorating techniques compatible with standard STAP implementation, including localised processing, localised processing with time-varying weights, equivalent uniform linear array transformation, angle-Doppler warping and higher-order angle-Doppler warping. The authors demonstrate very good performance for the higher-order angle-Doppler warping method applied to the chined radome shape, with peak adaptive SINR losses reduced from nearly 16-dB for the uncompensated case to 3-dB of loss consistent with performance attainable in a homogeneous clutter environment. The authors also find good performance for three-dimensional angle-Doppler warping over azimuth, elevation and Doppler when applied to the tapered canoe shape, with uncompensated losses of roughly 14-dB reduced to 3-dB, again a level compatible with STAP applied in a homogeneous clutter environment. The authors thus show that CFA STAP can yield performance similar to that of a conventional planar array when using appropriate compensation methods.

Analysis of global navigation satellite system position deviation under spoofing

Abstract: The position deviation in global navigation satellite system (GNSS) positioning, which is subject to spoofing, is analysed. A spoofer transmits GNSS-like signals to a navigation receiver and may cause a significant position deviation in navigation computation. Although GNSS receivers can be equipped with certain receiver autonomous integrity monitoring (RAIM) schemes to provide fault detection and isolation functions, it is possible that the misleading information because of spoofers may enter a GNSS receiver without being detected. As spoofers may inject erroneous pseudo-range measurements to the navigation receiver with a false message, it is important to assess the spoofing effect on the resulting position. An optimisation approach is adopted to determine the worst-case misleading message and the resulting position deviation. A vulnerability index against spoofing is defined for the assessment of the position deviation in a spoofed environment.

Direction of arrival estimation for uncorrelated and coherent signals with uniform linear array

Abstract: A novel direction of arrival (DOA) estimation method is proposed with uniform linear array when uncorrelated and coherent signals coexist. The DOAs of uncorrelated signals are first estimated using a new method of modified total least squares estimation of signal parameters via rotation invariance techniques. Afterwards, the contributions of uncorrelated signals are eliminated and a new matrix is constructed based on the spatial difference matrix. Then, the coherent signals can be resolved by performing the forward spatial smoothing scheme on the new matrix. The proposed method can resolve more signals than the array elements with good performance. Simulation results demonstrate the effectiveness and efficiency of the proposed method.

Improvement of high-frequency surface waves radar performances by use of multiple-input multiple-output configurations

Abstract: A multiple-input multiple-output (MIMO) configuration has been studied for communication applications, offering a lot of advantages to mitigate propagation effects because of multipath and fading environments. More recently, MIMO techniques in radar have been proposed. MIMO is discussed in the context of high-frequency surface waves radar (HFSWR). After a short introduction to the MIMO radar technique (a technique which is not new; the RIAS developed by ONERA was probably the first MIMO radar), explores two different applications are explored. The first application aims at improving the resolution and accuracy of a coastal radar, proposed here in a bistatic configuration. Such a radar operates with a wide sparse frequency band and with an equivalent wide aperture, taking advantage of the MIMO configuration. Simulation over a congested area of targets demonstrates the benefit of MIMO over the conventional HFSWR radar, especially in terms of separation of targets. The second application consists in a more practical ship-borne HFWSR configuration compatible with space time adaptive processing (STAP) to improve the detection of slow targets. In this case, a limited number of receiving channels is considered whereas STAP uses the degrees of freedom offered by the transmitting array. The MIMO-STAP is compared with a conventional STAP, showing that theoretical performances should not be affected by the MIMO configuration even if the signals are no longer perfectly orthogonal, because of Doppler shift, once scattered by moving targets.

Direction finding in spatially correlated noise fields with arbitrarily-spaced and far-separated subarrays at unknown locations

Abstract: A computationally simple azimuth-elevation direction finding algorithm in spatially correlated noise fields using two-far-separated subarray geometry (Li et al. 1995) is presented. We assume one subarray consists of multiple acoustic vector sensors, while another subarray comprises multiple pressure sensors. All sensors are arbitrarily placed at unknown locations. The authors firstly define a cross matrix to eliminate the effect of the spatially correlated noise. Then the so-called propagator method is used to estimate the steering vectors of acoustic vector sensors. Finally, a closed form, automatically paired azimuth-elevation angle estimates are derived. The proposed algorithm requires no eigen decomposition into signal or noise subspaces. In addition, the proposed algorithm does not need 2D iterative searching. Therefore the algorithm shows low computational complexity. Monte Carlo simulations are presented to verify the effectiveness of the proposed algorithm.

Non-adaptive multiple-input, multiple-output radar techniques for reducing clutter

Abstract: Multiple-input, multiple-output (MIMO) radars enhance performance by transmitting and receiving coded waveforms from multiple locations. This paper describes MIMO techniques that can be used to improve radar performance, especially in airborne Ground Moving Target Indicator (GMTI) applications. The authors begin by showing how MIMO techniques can lower airborne radar clutter to noise ratios (CNRs). This results in smaller losses when observing stationary or low-velocity targets. Next, the authors consider the implementation of MIMO radar modes using electronically scanned arrays (ESAs). Specifically, the authors show how MIMO techniques, applied to subarray-based ESAs, can cause high grating lobes and/or reduced search rates. To address this problem, the authors describe new space-time waveform coding techniques that can be used to improve performance. Two space-time waveform encoding approaches are proposed: (i) an overlapped virtual transmit subarray approach, and (ii) a beamspace MIMO approach. A third approach, involving conventional MIMO waveforms and irregular subarrays, is also briefly considered.