Measuring Range Rate

In high-frequency surface wave radar (HFSWR) systems, clutter is a common phenomenon that causes objects to be submerged. Space-time adaptive processing (STAP), which uses two-dimensional data to increase the degrees of freedom, has recently become a crucial tool for clutter suppression in advanced HFSWR systems. However, in STAP, the pattern is distorted if a clutter component is contained in the main lobe, which leads to errors in estimating the target angle and Doppler frequency. To solve the main-lobe distortion problem, this study developed a clutter-suppression method based on beam reshaping (BR). In this method, clutter components were estimated and maximally suppressed in the side lobe while ensuring that the main lobe remained intact. The results of the proposed algorithm were evaluated by comparison with those of standard STAP and sparse-representation STAP (SR-STAP). Among the tested algorithms, the proposed BR algorithm had the best suppression performance and the most accurate main-lobe peak response, thereby preserving the target angle and Doppler frequency information. The BR algorithm can assist with target detection and tracking despite a background with ionospheric clutter.

Mechanical vibration or rotation of a target or structures on the target may induce additional frequency modulations on the returned radar signal which generate sidebands about the target's Doppler frequency, called the micro-Doppler effect. Micro-Doppler signatures enable some properties of the target to be determined. In the paper, the micro-Doppler effect in radar is introduced and the mathematics of micro-Doppler signatures is developed. Computer simulations are conducted and micro-Doppler features in the joint time - frequency domain are exploited.

Attentions have been focused on the moving target detection in a high-resolution sea clutter. This study commences with a proposal of median-based estimator to estimate the power spectrum of high-resolution sea clutter by the time series observed in adjacent range cells and time intervals. The estimator provides a robust estimation when just a few aberrant time series happen in observation. Based on the estimator, a block-adaptive clutter suppression filter (BACSF) is designed to suppress the clutter prior to the pulse integration. Then, the residual clutter, the output of the BACSF, is modelled as spherically invariant random vector. Upon applying an adaptive normalised matched filter (ANMF) to the residual clutter, a residual clutter's ANMF detector is derived. Moreover, in high-resolution radar background, considering that the approximately stationary intervals of sea clutter and residual clutter are much shorter than the coherent processing interval, another heuristic block-ANMF detector is proposed. It can integrate more pulses and can achieve better performance than the ANMF detector does. This study concludes with the experiments of simulated target against the real sea clutter. The experimental results demonstrate that, when target's Doppler frequency is beyond strong clutter region, the ANMF detector and block-ANMF detector perform better in the residual clutter than in the clutter.

An interference improvement factor (IIF) is derived for a generalised square-law detector utilised for a radar application. This factor, which is a ratio of two quadratic forms, incorporates the effects of antenna beam shape as the radar beam scans over the target, interference due to receiver noise plus clutter and the target Doppler frequency. The IIF can be maximised to improve target detectability via eigenvalue, eigenvector techniques so that the optimal weights to be applied by a weighted integrator following the square-law device can be determined for an N-pulse batch. Numerical results are presented for a sea surveillance application.

Reduced-complexity multiple parameters estimation via toeplitz matrix triple iteration reconstruction with bistatic MIMO radar

For the Inverse Synthetic Aperture Radar (ISAR) imaging, the ISAR image obtained by the Range-Doppler (RD) or time-frequency analysis methods can not display the target's real shape due to its azimuth relating to the target Doppler frequency, thus the cross-range scaling is required for ISAR image. In this paper, a fast cross-range scaling method for ISAR is proposed to estimate the Rotational Angular Velocity (RAV). Firstly, the proposed method utilizes efficient Pseudo Polar Fast Fourier Transform (PPFFT) to transform the rotational motion of two ISAR images from two different instant time into translation in the polar angle direction. Then, a new cost function called integrated correction is defined to obtain the RAV coarse estimation. Finally, the optimal RAV can be estimated using the Bisection method to realize the cross-range scaling. Compared with the available algorithms, the proposed method avoids the problems of precision loss and high computational complexity caused by interpolation operation. The results of computer simulation and real data experiments are provided to demonstrate the validity of the proposed method.

A millimeter wave (MMW) pseudo random code continuous wave (PRC-CW) radar utilizing Doppler compensation is introduced. The novel hybrid transmitted waveform used in this radar combining single frequency pulse with pseudo random binary phase-coded signal is presented which makes consequent target detection through pulse compression independent of Doppler frequency. Doppler frequencies of targets are firstly estimated based on interpolated FFT in the time span of single frequency pulse and the Doppler compensated signal can be constructed. The effect of Doppler mismatch on the correlation detection can be eliminated by processing the compensated signal using conventional pulse compression-FFT, which makes the radar capable of short-range high-speed target detection. The theoretical analysis and simulation result demonstrate the validity of this technique.

When a hypersonic vehicle flies in the atmosphere, plasma sheath and trails are configured around the vehicle due to aerodynamic heating and ablation, which distort the radar echo signal and then influence the target range information and Doppler frequency extracted from the echoes. In order to examine the impact of plasma laminar wake on radar detection, this article is primarily aimed to establish a laminar wake echo model based on a linear frequency-modulated continuous wave (LFMCW) radar, which takes into account the reaction control system of laminar wake by employing the Born approximation solution and the characteristics of the inhomogeneous and nonunique velocity of the wake medium. An echo signal processing method is also developed, in which the stretch processing technique is combined with the keystone transform of the target range walk correction. Such a treatment not only reduces the sampling rate and bandwidth, but also eliminates the cross-range cells phenomenon caused by hypersonic; finally, the range-Doppler (RD) image of the wake is achieved by 2-D fast Fourier transform (2-D FFT) processing, and radar range and velocity measurement results in the presence of plasma are obtained.

When the target Doppler frequency in a radar homing missile crosses the main lobe clutter spectrum at the terminal phase of its flight, a large miss distance is induced. This paper presents the quantitative analysis on this clutter effect using a program named SAMS (Statistical Assessment of Missile Systems), which is a hierarchical and generalized version of the SLAM (Statistical Linearization Adjoint Method). A homing missile is represented by triple time constants, a limiter, a second-order missile airframe, and proportional navigation. The main lobe clutter is imposed on to this system along with the target random maneuver, glint, fading, and receiver noise. By processing the covariance propagation of the system equation and the adjoint system, the miss distance and the contribution of each noise are calculated. The results reveal that the clutter effect is maximized if the target Doppler frequency begins to cross the main lobe clutter spectrum 2 s prior to the terminal time, and it is largely enhanced if the target random maneuver is combined. These effects are reduced, however, if the missile lateral acceleration capability is increased or the target lateral acceleration decreased. The radome effect is also analyzed by adding the related feedforward loop to the original system, which makes a considerable change in the miss distance.

Moving targets submerged in clutter can be more readily detected by range-gated filtering techniques. Range-gated filtering is a two-dimensional process in which target Doppler frequency and range are desired output quantities. Optical data processing techniques are inherently multidimentsional. An experimental system using a He-Ne laser source and film transparencies representing radar echoes gave output patterns in agreement with theoretical predictions. Major advantages of an optical filter are simplicity and relatively small size.

This paper mainly deals with the detection problem of micro-motion target in image domain, and presents a novel method based on micro-Doppler characteristics and back-projection imaging. Firstly, the Doppler frequency and range of micro-motion target are obtained through MTI filter and FFT for the target echo. Then back-projection imaging is applied to generate the image of micro-motion target. To do so, the effect of stationary target is removed and the micro-motion target is separated from the stationary target. The experiment results validate this method, and demonstrate that the non-coherent imaging outperforms the coherent one.

In high frequency surface wave radar (HFSWR), Doppler frequencies of the vessels targets may overlap the first order Doppler frequencies from the sea clutter interference. Therefor it is hard to discover the vessel targets and estimate direction of arrive (DOA) of the ship targets. In this paper, the target direction finding method based on fractional Fourier transform (FRFT) was introduced for uniform acceleration/deceleration target, which used the frequency peculiarity difference between the targets and the first order sea clutter. Before the target DOA estimation, sea clutter were suppressed by FRFT method. The effectiveness of the method was verified by the simulations. The result demonstrated our method can estimate the DOA of targets in first order Doppler spectrum of sea clutter.

A robust STAP method for airborne radar based on clutter covariance matrix reconstruction and steering vector estimation

The Gaussian noise model and estimators based on least squares (LS) are widely used in target localisation with distributed multiple‐input multiple‐output (MIMO) radar because of their computational efficiency. However, the accuracy of existing LS‐based target localisation algorithms deteriorates sharply in the presence of outliers in the measurements. Thus, a robust solution is developed based on the ‐norm minimisation criterion and iteratively reweighted least squares (IRLS) for locating a moving target with impulse noise using the angle of arrival (AOA), time delay (TD), and Doppler shift (DS) measurements. First, the AOA, TD, and DS measurement noise models are developed based on the α‐stable distribution. Then, the localisation problem is transformed into an ‐norm minimisation problem by linearising the AOA, TD, and DS measurement equations. Finally, the ‐norm minimisation problem is solved using an IRLS method to obtain the target position and estimate the velocity. Moreover, the optimum of the norm order (p) and the Cramér–Rao lower bound for the target position and velocity estimation are derived under α‐stable distributed measurement noise. The simulation results demonstrate that the developed algorithm offers higher accurascy and robustness than the existing ones in the presence of measurement outliers.

In the field of marine robotics, the problem of rangebased underwater target localization can be defined as that of localizing an unknown — fixed or moving — target from a surface vehicle called the tracker, using range information available about the target. In this set-up, the motion of the tracker (relative to the target) has a significant effect on its ability to localize the target. In general, without any prior knowledge about the target motion, this is a very challenging problem and one that requires, at the outset, a thorough observability analysis of the model adopted for localization system design. For a restricted class of target motions generated using constant linear speed and piecewise constant course rates throughout a given observation window, the target's initial position, constant speed, initial course angle, and course rate, completely characterize its motion. The conditions under which one can estimate any combinations of these four parameters using range information has not been fully studied, except for a simple isolated case where the initial target position is the only unknown parameter. In this paper, using range information, we address the observability properties of the target localization problem for a target moving along a straight line or an arc of a circumference with constant linear and angular speeds on a given observation window. In the first case there are three target parameters (initial position, linear speed, and course angle), while in the second case there are four (initial position, linear speed, angular speed, and course angle). To make the problem mathematically tractable, we consider simple kinematics models for the tracker (we assume a constant linear speed) and target with planar position and course angle as state variables. Under these conditions, for the aforementioned two cases, we investigate the observability properties of range-based target localization problem for various target parameter combinations. In particular, when the target is moving along a straight line, for most of the unknown target parameter combinations, we show that observability can be achieved by a nonzero constant tracker's course rate, which is a simple condition. In the case where the target moves along a circular path, with the knowledge of the angular speed, we derive sufficient conditions on the trackers input to achieve observability, which are more demanding and less straightforward, and do not lend themselves to a simple geometrical explanation.