A small vessel detection using a co-located multi-frequency FMCW MIMO radar

Small vessels detection is a known issue due to its low radar cross section (RCS). An existing shore-based vessel tracking radar is for long-distance commercial vessels detection. Meanwhile, a vessel-mounted radar system known for its reliability has a limitation due to its single radar coverage. The paper presented a co-located frequency modulated continuous waveform (FMCW) maritime radar for small vessel detection utilising a multiple-input multiple-output (MIMO) configuration. The radar behaviour is numerically simulated for detecting a Swerling 1 target which resembles small maritime’s vessels. The simulated MIMO configuration comprised two transmitting and receiving nodes. The proposal is to utilize a multi-frequency FMCW MIMO configuration in a maritime environment by applying the spectrum averaging (SA) to fuse MIMO received signals for range and velocity estimation. The analysis was summarised and displayed in terms of estimation error performance, probability of error and average error. The simulation outcomes an improvement of 2.2 dB for a static target, and 0.1 dB for a moving target, in resulting the 20% probability of range error with the MIMO setup. A moving vessel's effect was observed to degrade the range error estimation performance between 0.6 to 2.7 dB. Meanwhile, the proposed method was proven to improve the 20% probability of velocity error by 1.75 dB. The impact of multi-frequency MIMO was also observed to produce better average error performance

Wavelet Technique Implementation in Forward Scattering Radar (FSR) Ground Target Signal Processing

Micro-sensor Forward Scattering Radar (FSR) is a network system used to detect and classify any ground target (personnel, vehicle) that is crossing by or entering its coverage area. The efficiency of the classification performance is highly dependent on the information extracted from the measured signal. The choice of transformation techniques that can reveal the information of the target should be chosen carefully. Hence, this reported work analyzed the implementation of Haar and Meyer Wavelet Technique (WT) that gives more detailed scales and variation information from the measured signals. The results from the wavelet technique show that we could find the similarity between signals of each target and dissimilarity between different targets

Spectrum averaging in a MIMO FMCW maritime radar for a small fluctuating target range estimation

Detection of a small maritime target has been challenging in radar signal processing due to the object size near the water surface. This paper provides an alternative detection method for a small fluctuating target by deploying a frequency modulated continuous waveform (FMCW) in a multiple-input multiple-output (MIMO) configuration. The work proposed a MIMO FMCW radar with a frequency offset between transmitted sub-bands, and the spectrum averaging (SA) scheme to combine the multiple received signals. A MIMO with an equal number of transmit and receive nodes were employed, and transceivers were co-located. The frequency-offset introduced an interval band between MIMO sub-signals to avoid interference and overlapping. The work observed range error parameters of a small fluctuating target. The result reveals that applying the SA with and without an interval band produced a better performance against signal-to-noise ratio (SNR) in terms of probability of range error and range error mean, through numerical simulations and experiments. However, MIMO caused an incremental computational complexity with the number of nodes based on Fast Fourier Transform (FFT) algorith

An evaluation of cots-based radar for very small drone sense and avoid application

The use of very small unmanned aerial vehicles (UAVs) are increasingly common these days but its applications are limited to the pilot line-of-sight view. To extend its use beyond the pilot view, UAVs need to be equipped sense and avoid (SAA) system to avoid potential collisions. However, the development of SAA for very small drones is still in the infancy stage mainly due to the high cost of design and development for reliable range sensors. Recent developments of very small size and lightweight commercial off-the-shelf (COTS)-based radar systems may become a crucial element in very small drone applications. These types of radars are primarily developed for industrial sensing but can be adapted for applications such SAA. Thus, this paper contributes to the survey of a miniature and lightweight radar sensor to assist the SAA development. The focus of this paper is to analyse the eligibility of a COTS-based radar in detecting very small drones. For this purpose, we used a frequency-modulated continuous radar (FMCW) developed by Infineon Technologies. Field test results show the real-time capability of the radar sensor to detect the very small drones within ± 0.5 meters in static and dynamic conditions

Maritime radar: a review on techniques for small vessels detection

Maritime radar is an essential technology for observation and tracking systems in various marine applications. In comparison with terrestrial radar systems, maritime radar faces the challenge of large clutter signals, contributed by sea waves. This problem becomes more critical when the system is detecting relatively small vessels, where the probability of detection is reduced due to small radar cross section (RCS) of the vessels themselves. This paper presents a review of recent techniques in maritime radar, developed to overcome this issue, discussing several aspects such as (i) system topology, (ii) radar waveforms, and (iii) detection algorithms. Considering the recent works in this area, several recommendations for future works are presented to further improve the performance of modern maritime radar detecting small vessels

Automatic vehicle classification in a low frequency forward scatter micro-radar.

Forward Scattering Radar (FSR) is a special case of bistatic radar configuration where the desired radar signal is formed via the shadowing of the direct (transmitter-to-receiver) signal by the target body. FSR offers a number of interests including an inherent ability to detect stealth target, absence of signal fluctuations, reasonably simple hardware, enhanced target radar cross-section (RCS) compared to traditional radar and capability to use Inverse Synthetic Aperture algorithms for Automatic Target Classification (ATC). Of course as any system FSR has its own drawbacks and limitations. This thesis presents the research results on development of ATC algorithm under a variety of external factors such as clutter and target's trajectories uncertainties. The peculiarity of this research are that the FSR operates at a low (VHF and UHF) frequency bands that in a strict sense does not correspond to an optical region for vehicles like targets and the system operate with omnidirectional antennas. There is no previous research considered this practically important case. The algorithm is developed based on Fourier transform, Principal Component Analysis (PCA) and K-Nearest Neighbour (KNN) classifier - for features extraction, transformation and classification, respectively. The ATC system is integrated with coherent signal processing algorithm in order to estimate target’s motion parameters (i.e speed) prior to spectra normalisation process. The analytical and modelling results are experimentally confirmed. As ATC performance degraded when high level of clutter is present, cluttercompensated ATC model is introduced and its classification performance is analysed using measured signals with added simulated clutter

Power comparisons of the seven methods as a function of <i>c</i>² for the six models.

<p>The total number of phenotypes is <i>K</i> = 8, <i>ρc</i>² = 0.1, <i>β</i> = 0.1, and <i>MAF</i> = 0.3. The p-values of WCmulP and SHet are evaluated using 1,000 permutations, the p-values of other methods are evaluated using asymptotic distribution. The power of all of the seven methods is evaluated using 1,000 replicated samples at a significance level of 0.01.</p