Measurements and analysis of multistatic and multimodal micro-Doppler signatures for automatic target classification

The purpose of this paper is to present an experimental trial carried out at the Defence Academy of the United Kingdom to measure simultaneous multistatic and multimodal micro-Doppler signatures of various targets, including humans and flying UAVs. ewline Signatures were gathered using a network of sensors consisting of a CW monostatic radar operating at 10 GHz (X-band) and an ultrasound radar with a monostatic and a bistatic channel operating at 45 kHz and 35 kHz, respectively. A preliminary analysis of automatic target classification performance and a comparison with the radar monostatic case is also presented

Train Monitoring using GSM-R Based Passive Radar

Train detection technologies are universal to all modern railway signal and control systems. They are essential for managing the movement of vehicles across entire transport networks, and to ensure their safe operation. In this paper we investigate the feasibility of a new train monitoring capability based on passive radar technology. The system exploits signal transmissions from the railways’ GSM-Railway (GSM-R) radio communications infrastructure, and has the potential to determine the positions and velocities of trains over any section of a railway network where there is GSM-R coverage. A theoretical ambiguity function analysis on directly measured GSM-R waveforms suggest that targets can be detected with axial range resolutions of approximately 850 m, and velocities down to less than 1 mph. To demonstrate proof-of-concept, a series of experiments were carried out using a software-defined GSM-R passive radar system. The results show the first detections of trains at bistatic ranges of just over 1 km moving at various speeds. There are now hundreds of thousands of miles of railway track covered by GSM-R globally, with many more countries planning to rollout systems nationally. The results therefore imply that GSM-R based passive radar technology could be used to develop low-cost train monitoring capabilities worldwide alongside the existing GSM-R radio communications infrastructure

Signs of life detection using wireless passive radar

Non-contact devices for monitoring signs of life have attracted a lot of attention in recent years for applications in security, emergency and disaster situations. Current devices however, generally utilize bespoke active systems to transmit large bandwidth signals. In this paper, a real-Time phase extraction method based on passive Wi-Fi radar is proposed for detecting the chest movements associated with a person breathing. Since the monitored movements are of low amplitude and small Doppler shift, this method uses the phase variation rather than traditional range-Doppler processing. The processing is based on time domain cross correlation, with the addition of a Hampel filter for outlier detection and removal. In this paper the basic passive Wi-Fi model and limitations of traditional cross ambiguity function for signs of life detection are first introduced. The phase extraction method is then described followed by experimental results and analysis. Detection of breathing for a stationary person is shown in both in-room and through wall scenarios using both the Wi-Fi beacon and data transmissions. This is believed to be the first demonstration of signs of life detection using phase extraction in passive radar and extends the capability of such systems into a wide range of new applications

A low-cost through-the-wall FMCW radar for stand-off operation and activity detection

In this paper we present a new through-wall (TW) FMCW radar system. The architecture of the radar enables both high sensitivity and range resolutions of <1.5 m. Moreover, the radar employs moving target indication (MTI) signal processing to remove the problematic primary wall reflection, allowing higher signal-to- noise and signal-to-interference ratios, which can be traded-off for increased operational stand-off. The TW radar operates at 5.8 GHz with a 200 MHz bandwidth. Its dual-frequency design minimises interference from signal leakage, and permits a baseband output after deramping which is digitized using an inexpensive 24-bit off-the-shelf sound card. The system is therefore an order of magnitude lower in cost than competitor ultrawideband (UWB) TW systems. The high sensitivity afforded by this wide dynamic range has allowed us to develop a wall removal technique whereby high-order digital filters provide a flexible means of MTI filtering based on the phases of the returned echoes. Experimental data demonstrates through-wall detection of individuals and groups of people in various scenarios. Target positions were located to within ±1.25 m in range, allowing us distinguish between two closely separated targets. Furthermore, at 8.5 m standoff, our wall removal technique can recover target responses that would have otherwise been masked by the primary wall reflection, thus increasing the stand-off capability of the radar. Using phase processing, our experimental data also reveals a clear difference in the micro-Doppler signatures across various types of everyday actions

Physical Activity Sensing via Stand-Alone WiFi Device

WiFi signals for physical activity sensing shows promising potential for many healthcare applications due to its potential for recognising various everyday activities, non-invasive nature and low intrusion on privacy. Traditionally, WiFi-based sensing uses the Channel State Information (CSI) from an offthe- shelf WiFi Access Point (AP) which transmits signals that have high pulse repetition frequencies. However, when there are no users on the communication network only beacon signals are transmitted from the WiFi AP which significantly deteriorates the sensitivity and specificity of such systems. Surprisingly WiFi based sensing under these conditions have received little attention given that WiFi APs are frequently in idle state. This paper presents a practical system based on passive radar technique which does not require any special setup or preset firmware and able to work with any commercial WiFi device. To cope with the low density of beacon signal, a modified Cross Ambiguity Function (CAF) has been proposed to reduce redundant samples in the recorded. In addition, an external device has been developed to send WiFi probe request signals and stimulate an idle AP to transmit WiFi probe responses thus generate usable transmission signals for sensing applications without the need to authenticate and join the network. Experimental results prove that proposed concept can significantly improve activity detection and is an ideal candidate for future healthcare and security applications

Respiration and Activity Detection based on Passive Radio Sensing in Home Environments

The pervasive deployment of connected devices in modern society has significantly changed the nature of the wireless landscape, especially in the license free industrial, scientific and medical (ISM) bands. This paper introduces a deep learning enabled passive radio sensing method that can monitor human respiration and daily activities through leveraging unplanned and ever-present wireless bursts in the ISM frequency band, and can be employed as an additional data input within healthcare informatics. Wireless connected biomedical sensors (Medical Things) rely on coding and modulating of the sensor data onto wireless (radio) bursts which comply with specific physical layer standards like 802.11, 802.15.1 or 802.15.4. The increasing use of these unplanned connected sensors has led to a pell-mell of radio bursts which limit the capacity and robustness of communication channels to deliver data, whilst also increasing inter-system interference. This paper presents a novel methodology to disentangle the chaotic bursts in congested radio environments in order to provide healthcare informatics. The radio bursts are treated as pseudo noise waveforms which eliminate the requirement to extract embedded information through signal demodulation or decoding. Instead, we leverage the phase and frequency components of these radio bursts in conjunction with cross ambiguity function (CAF) processing and a Deep Transfer Network (DTN). We use 2.4GHz 802.11 (WiFi) signals to demonstrate experimentally the capability of this technique for human respiration detection (including through-the-wall), and classifying everyday but complex human motions such as standing, sitting and falling

Evidence-based medicine and values-based medicine : partners in clinical education as well as in clinical practice

The best clinical decisions are based on both evidence and values in what is known as the ‘twofeet principle’. Anecdotally, educationalists find teaching clinicians to become more evidence based is relatively simple in comparison to encouraging them to become more values based. One reason is likely to be the importance of values awareness. As valuesbased practice is premised on a mutual respect for the diversity of values, clinicians need to develop the skills to ascertain patient values and to get in touch with their own beliefs and preferences in order to understand those at play in any consultation. Only then can shared decision-making processes take place within a shared framework of values. In a research article published in BMC Medicine, AltamiranoBustamante and colleagues highlight difficulties that clinicians face in getting in touch with their own values. Despite finding that healthcare personnel’s core values were honesty and respect, autonomy was initially low ranked by participants. One significant aspect of this work is that this group has demonstrated that the extent to which clinicians value ‘autonomy’ and ‘openness to change’ can both be positively influenced by well designed education

Multistatic Radar: System Requirements and Experimental Validation

Multistatic radar provides many advantages over conventional monostatic radar, such as enhanced information on target signatures and improvements in detection which are due to the multiple perspectives and differences in the properties of clutter. Furthermore, the fact that receive-only multistatic nodes are passive may be an advantage in military applications. In order to quantify potential performance benefits of these advantages a comprehensive understanding of target and clutter behaviour in multistatic scenarios is necessary. However, such information is currently limited because bistatic and multistatic measurements are difficult to make, their results depend on many variables such as multistatic geometry, frequency, polarization, and many others, and results from previous measurements are likely to be classified for military targets. Multistatic measurements of targets and clutter have been performed over the past few years by the NetRAD system developed at the University College London and the University of Cape Town. A new system, NeXtRAD, is now being developed in order to investigate some of the many aspects of multistatic radar. This paper discusses the results obtained with the previous system and the lessons learnt from its use. These points are then discussed in the context of the new radar, defining key important factors that have to be considered when developing a new multistatic radar system