Optimum coherent integration time for a surface target with periodic acceleration

The detection performance of high frequency surface wave radar is impacted by the ionospheric clutter. In order to suppress the ionospheric clutter, it is important to research the physical mechanism of ionosphere. In this paper, it is demonstrated, convincingly for the first time, the chaotic dynamics of the ionospheric clutter. The results are obtained using the actual data collected from a series of experiments in Weihai Radar Station, China. The study includes the stationarity and nonlinearity test, phase-space reconstruction, correlation dimension analysis and Lyapunov exponents analysis. And finally, it is found that ionospheric clutter in HFSWR is a chaotic dynamical process with relatively few degrees of freedom, in contrast to the stochastic approach where the ionospheric clutter is viewed as a random process with a large number of degrees of freedom[1]. Also, this new approach will further provide an original way to analyse the ionospheric clutter suppression method.

In this paper, we consider the exploitation of long coherent integration times for improving the detection of small drones in a DVB-S based Passive Radar (PR). In fact, since these low-flying objects are characterized by very small RCS values, their detection is challenging especially when using DVB-S signals as source of opportunity, typically received with low power levels. In this work, in order to benefit from the use of extended coherent integration times, the target range and Doppler migration effects have been properly compensated. Then, the effectiveness of the adopted detection scheme has been tested against real data collected by a multi-polarimetric DVB-S based PR receiver developed at Sapienza University of Rome. The reported results show that the coherent integration time can be increased up to a few seconds thus improving the drone detection capability of the considered system.

A method for adaptively determining a desirable coherent integration time for radar observations of a moving clutter target is examined. A signal model appropriate for such measurements is first defined, along with an approach for estimating the coherence time from measured data. This coherence time estimate is then used as the coherent integration time in a reprocessing of the measured data. Simulations are shown that illustrate the potential advantages of this approach in reducing the variance of the clutter power estimate, particularly at low clutter to noise ratios, as compared to a purely incoherent integration. However the initial correlation time estimator examined is found to be ineffective, so that alternate strategies are required to obtain the desired performance improvements.

An understanding of the parameters affecting the high frequency surface wave radar (HFSWR) cross sections of the ocean surface is essential to employing such formulations in remote sensing models. Available techniques to date have not explicitly included the effect of antenna motion on the ocean clutter spectra derived from HF Doppler radar data. Here, a model, which assumes the incident radiation to be a simple pulse and accounts for the fact that there may be antenna motion in the radar look direction, is presented. Simulations indicate that the motion of the antennas may give rise to additional, significant spectral content which cannot be ignored when the Doppler spectra are used for ocean parameter estimation.

Auto ship detection for high frequency (HF) skywave over-the-horizon (OTH) radar, being a valuable application, has not been achieved virtually within short coherent integration times (CITs). Because the ships' lines in the spectrum can be covered by the ocean clutter's easily as a result of the poor resolution, which attenuates the validities of ocean clutter suppression algorithms. Besides, when the backscatter echo of ocean clutter becomes complicated, which can often be caused by the complex environmental factors, the performance of ocean clutter suppression algorithms also degrades. To achieve auto ship detection within short CITs, a scheme employing algorithms including Orthogonal Matching Pursuit (OMP), eigenvalue-decomposition (EVD) and constant false alarm rate (CFAR) processor, called OEC scheme which is the acronym for the methods applied, is proposed in this paper. Simulations approves the validation of the scheme.

In order to reduce the Doppler spread effect caused by ionospheric disturbance, sky wave over-the-horizon radar often detects ships in a short coherent integration time (CIT). In short CIT, an effective means to detect ships is clutter suppression. Through the analysis of the real data, it is found that the sea clutter has a strong correlation when the sea state is relatively stable, whether in long CIT or short CIT. To avoid estimating clutter subspace dimension and clutter cancellation times of the available methods, an adaptive clutter suppression method based on sea clutter correlation is proposed. This method does not need to estimate the parameters of the clutter, even when the Doppler frequency of the ship target is close to the sea clutter, the target can be detected. Theoretical analysis and real data processing indicate that the proposed method can detect ship target effectively.

On the basis of analysis of mechanism of ocean clutter production, an improved orthogonal vector spectral estimation method based on signal-subspace was proposed to use for the ship target detection with short coherent integration times(CITs) in the offing background. With this method, the sample data correlation matrix of the echo signal is treated by the forward/backward spatial (FB) smoothing technique firstly, and whose eigen-vector corresponding to the maximum eigenvalue is arranged as an unsymmetrical matrix by definite rule and there are also signal-subspace and orthogonal subspace in the singular value decomposition of the eigen-matrix, which can be used to ship target detection in the OTHR. Simulations proved that it is of higher resolution, and there is no sidelobes, with which the ship target can be detected efficaciously under the condition of CITs in the offing background.

We have developed and demonstrated the Keystone format to simultaneously remove linear range migration for all targets regardless of their velocities. Higher order motion and under sampling foldover can be removed by hypotheses. The authors present an approach to radar matched filtering which can produce simultaneous high range and high Doppler resolution matched filter outputs. The new matched filter coherently integrates the radar data even though the target scatterers move through many range resolution cells during the coherent integration time.

HF surface-wave radars (HFSWRs) offer two distinct advantages when used over the sea: with vertical polarization, they see beyond the horizon, and the interaction of their signals with ocean waves is simple and well understood. As a result, many HFSWR research test programs were conducted in the U.S., beginning 35 years ago. This author was fortunate to have been immersed in these programs from the beginning. Early projects by the Defense Department focused on military target surveillance: ships, aircraft, and missiles. In the mid-70s, their potential was explored for environmental measurements: surface currents and sea state. Why after 35 years of testing and evaluation are none found in operational service today, except those made by CODAR for environmental monitoring? I discuss this question in the present paper.

In the signal structure design of new global navigation satellite system (GNSS), the ideas of secondary/tiered code was introduced. However, due to the inherent vulnerability of satellite navigation signal, frequency interference (RFI) has become a potential threat. The continuous wave interference (CWI) has become one of the most serious interference types for the characteristics of power concentration, multiple types and wide distribution of the interference source. The impact assessment of CWI on the performance of navigation signals has become a hot spot of research. However, the existing assessment method lacks the quantitative evaluation for the effect of the secondary code on signal performance in the presence of CWI. To solve the above problems, the impact of tiered codes with different length on signal power spectrum was analyzed firstly, and then influence of tiered codes on tracking performance by discrete spectrum carrier-to-noise ratio was analyzed. The experimental results show that the traditional analysis model based on continuous spectrum is no longer suitable for navigation signal performance analysis under the condition of CWI; the smaller the line distance is, the two times the code period is doubled and the line spacing is 0.1 times that of the original; and when coherent integration time doubles and the tracking performance deteriorates 2–3 dB; and when length of tiered code increase, the tracking performance can improve 2–3 dB; and short coherent integration time and long tiered code should be used in receiver design. A compromise needs to be made between these two parameters to ensure the tracking performance under CWI and the robustness of receivers. The proposed method can provide effective theoretical guidance for the development of the new GNSS signal receiver.

Range walk of the fourth generation fighters echo for traditional radar signal processing is a serious problem in the long coherent integration time. To solve the problem, a novel coherent Radon transform based weak target detection algorithm for metric-band phased array radar is proposed. First the echo signal model of supersonic weak target is provided, and the characteristic of range walk is analyzed. Based on this, the coherent Radon transform based long term coherent integration algorithm along the range walk line is presented. Finally, the performance of target detection and parameter estimation of the algorithm are analyzed by the simulation experiments, which suggest that the proposed algorithm has better detection performance compared with Hough transform method and MTD method. (5 pages)

Computer analysis and simulation routines have been used to maximize the area surveillance rate by evaluating several detection schemes and by finding an optimum set of N/sub i/ (number of noncoherent integration periods), SNR (signal-to-noise ratio), and T/sub ci/ (coherent integration time) values that minimize the dwell time. An example comparison between 4-out-of-4 and 2-out-of-3 detection shows a 51% improvement when the dwell time is optimized. A comparison between 3-out-of-3 and 2-out-of-3 detection with dwell-time optimization shows a 42% improvement. A routine has been used to maintain the false-alarm time nearly constant over a large access area. The routing has little effect on the area coverage rate. The coverage rate is very sensitive to the N/sub i/, T/sub ci/ set used (holding output probability of detection constant) but rather insensitive to the false-alarm number used.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Long line arrays of many elements present special problems for adaptive beamforming. The long travel time for an endfire signal to traverse the array requires the use of narrow frequency bins to avoid a significant phase change within a frequency bin. The narrow beamwidth near broadside makes the array sensitive to small bearing charges that occur within the coherent integration time so that adaptation must take place rapidly. These two effects combine to cause a snapshot-starved situation. A beam-based adaptation approach is suggested in which the first step is to form shaded conventional far-field beams. This is followed by a sectorized adaptive combination of beams in a sector to provide adaptive near-field and far-field beams. For a sector near broadside where the beams are very narrow and sensitive to motion but the travel time across the array is short, less temporal averaging and more frequency averaging is used. Near endfire, where the beams are wide but the travel is long, narrow frequency beams are used with longer temporal averaging. The approach is applied to the case of strong far-field interference masking a weak near-field signal. The approach is computationally efficient as well as providing improved snapshot support for adaptation.

A combined Position-Reflectometry Galileo receiver on board a low cost unmanned aerial platform (UAV) was developed in the framework of the Combined Positioning-Reflectometry Galileo Code Receiver for Forest Management project (COREGAL) with the main aims of evaluating the accurate positioning in areas where no GNSS ground infrastructures are available and of investigating the forest biomass mapping. In this context, the Soil and Vegetation Reflection Simulator (SAVERS) was employed to simulate GNSS-R data in order to analyze the GNSS-R sensitivity to biomass, to create a Look Up Table (LUT) of GNSS-R reflectivity and to carry out a biomass retrieval test. SAVERS simulated the mean power of the reflected GNSS-R signals by applying the integral bistatic equation taking into account the scattering contributions from soil and vegetation. It was shown that the GNSS-R sensitivity to forest biomass can be enhanced by filtering out the incoherent component of the signal, i.e. by using a long coherent integration time. A LUT was created by running SAVERS for a realistic range of the input parameters. Moreover, a GNSS-R synthetic dataset was generated for the case of a cork oak open forest in Portugal and a retrieval test was carried out. A neural network with two hidden layers was trained on the LUT and the forest biomass was estimated from the synthetic data. The biomass mean retrieval error was approximately 10 t/ha.

As a special system of early warning radar, high-frequency sky-wave over-the-horizon (OTH) radar usually needs to detect sea and airborne targets in the same direction simultaneously. However, the long coherent integration time (CIT) required by the sea target makes the echo data about high-speed moving airborne target in the same direction incompletely coherent, which is not conductive to the detection and tracking of airborne target. To overcome this problem, this paper proposes a novel track-before-detect (TBD) algorithm for airborne target. Firstly, the motion prior knowledge of the airborne target is utilized to select the number of pulses in the CIT to perform coherent integration processing. Then TBD based on dynamic programming (DP-TBD) technique is used to realize the noncoherent integration for the detection and tracking of the airborne target. Simulation results show that compared with the traditional method, the proposed algorithm effectively improve the detection and tracking performance of the airborne target.