Multi-Person Motion Tracking via RF Body Reflections

Recently, we have witnessed the emergence of technologies that can localize a user and track her gestures based purely on radio reflections off the person's body. These technologies work even if the user is behind a wall or obstruction. However, for these technologies to be fully practical, they need to address major challenges such as scaling to multiple people, accurately localizing them and tracking their gestures, and localizing static users as opposed to requiring the user to move to be detectable. This paper presents WiZ, the first multi-person centimeter-scale motion tracking system that pinpoints people's locations based purely on RF reflections off their bodies. WiZ can also locate static users by sensing minute changes in their RF reflections due to breathing. Further, it can track concurrent gestures made by different individuals, even when they carry no wireless device on them. We implement a prototype of WiZ and show that it can localize up to five users each with a median accuracy of 8-18 cm and 7-11 cm in the x and y dimensions respectively. WiZ can also detect 3D pointing gestures of multiple users with a median orientation error of 8 -16 degrees for each of them. Finally, WiZ can track breathing motion and output the breath count of multiple people with high accuracy

TROPHY: A Topologically Robust Physics-Informed Tracking Framework for Tropical Cyclones

Tropical cyclones (TCs) are among the most destructive weather systems. Realistically and efficiently detecting and tracking TCs are critical for assessing their impacts and risks. Recently, a multilevel robustness framework has been introduced to study the critical points of time-varying vector fields. The framework quantifies the robustness of critical points across varying neighborhoods. By relating the multilevel robustness with critical point tracking, the framework has demonstrated its potential in cyclone tracking. An advantage is that it identifies cyclonic features using only 2D wind vector fields, which is encouraging as most tracking algorithms require multiple dynamic and thermodynamic variables at different altitudes. A disadvantage is that the framework does not scale well computationally for datasets containing a large number of cyclones. This paper introduces a topologically robust physics-informed tracking framework (TROPHY) for TC tracking. The main idea is to integrate physical knowledge of TC to drastically improve the computational efficiency of multilevel robustness framework for large-scale climate datasets. First, during preprocessing, we propose a physics-informed feature selection strategy to filter 90% of critical points that are short-lived and have low stability, thus preserving good candidates for TC tracking. Second, during in-processing, we impose constraints during the multilevel robustness computation to focus only on physics-informed neighborhoods of TCs. We apply TROPHY to 30 years of 2D wind fields from reanalysis data in ERA5 and generate a number of TC tracks. In comparison with the observed tracks, we demonstrate that TROPHY can capture TC characteristics that are comparable to and sometimes even better than a well-validated TC tracking algorithm that requires multiple dynamic and thermodynamic scalar fields

Registration of Airborne Infrared Images using Platform Attitude Information

In current warfare scenario stealth and passive threat detection capabilities are considered as prime requirements to accomplish desired mission by the fighter aircrafts. To improve the stealth of an aircraft, the trend is towards detecting threats with the help of passive sensors (Electro Optic or Infrared). Current situation caters for systems like Infra-red Search and Track (IRST) and Passive Missile Warning Systems (PMWS). IRST system is a passive target detection system, used for detecting aerial & ground targets. PMWS is a threat detection system used for detecting missiles approaching towards aircraft. Both of these systems detect targets of interest by processing IR images acquired in mid-IR region. The prime challenge in IRST system or PMWS is detecting a moving target of size typically 1~2 pixels in acquired image sequences. The temporal change caused by moving target in consecutive frames can be considered as one important factor to detect them. The temporal change caused by moving target is identified through absolute frame differencing of successive frames. This principle has limitation in application to IRST & PMWS as the imaging sensor with the aircraft is moving. This motion also imparts temporal change in the acquired images. In this paper authors are proposing a method for removing the temporal change caused by the platform motion in two consequently acquired frames using registration process.  The proposed method uses the platform attitude information at frame sampling times. Authors have analyzed the sensitivity of registration process to noisy platform attitude information.Defence Science Journal, 2014, 64(2), pp. 130-135. DOI: http://dx.doi.org/10.14429/dsj.64.546

Narrowband AM interference cancellation for broadband multicarrier systems

We consider an overlay system where narrowband AM signals interfere with a broadband multicarrier system. To reduce the effect of the AM narrowband interference on the multicarrier system, we propose a low-complexity algorithm to estimate the AM narrowband interference. Analytical expressions for the performance of this estimator are derived and verified with simulations. The performance of this estimator, however, degrades when the number of interferers increases. To improve the algorithm, we adapt it such that the interferers are estimated in a successive way. The proposed estimators are able to produce accurate estimates of the frequencies, and track the time-varying amplitudes of the AM signals. The estimators can reduce the power of the AM signal to a level that is approximately 20 dB lower than the multicarrier power, independently of the AM signal power