KEYWORDS: Radar, Explosives, Ground penetrating radar, Unattended ground sensors, General packet radio service, Standoff detection, Improvised explosive device detection, X band, Acoustics, Signal to noise ratio
AKELA Inc. is a small company located in California that specializes in developing unique radar systems for the DoD and other government customers. Most of our research is focused on standoff through the wall (STTW) sensing and ground penetrating radar (GPR) over an ultra wide frequency range. Our systems range in size from a briefcase up to a truck-mounted antenna array. While many of the systems are monostatic, AKELA has also built distributed systems for perimeter monitoring and bistatic RCS measurements. This presentation will give an overview of AKELA’s current and past research programs in the STTW and GPR fields.
Ground based, mobile surface anomaly sensing and detection is a critical area of research in explosive hazard detection as well as local situational awareness and even autonomous operations. Increasingly, achieving reliable detection is coming to rely on a suite of different (often orthogonal) sensing modalities from optical to infrared to lidar and radar. Radar is of particular interest because it offers advantages when attempting to detect obscured surface anomalies and has the potential for large observation areas. Radar’s chief disadvantage in this context is that limited physical antenna aperture degrades the spatial localization of scattering returns. This is particularly troubling in highly cluttered surface environments. To address this shortcoming of spatial localization of scattering returns, this paper discusses the use of a MIMO X-band radar system configured in a high-resolution side-looking instantiation. By configuring the system this way it can be operated in a traditional stripmap synthetic aperture mode and since it is a MIMO array it has vertical aperture allowing for three-dimensional imagery to be formed. This paper details system elements, configuration and operation of a high resolution ground based, mobile MIMO X-band radar for side-looking anomaly detection. The system operates in X-band and utilizes a digitally synthesized frequency modulated continuous waveform. The system has previously been configured for forward looking mobile anomaly detection. The work presented in this paper is concerned with synthesizer and radio frequency electronics upgrades, side-looking specific configuration issues and image formation issues. Example side-looking three-dimensional imagery is shown using canonical calibration targets.
Radar based detection of human targets behind walls or in dense urban environments is an important technical challenge with many practical applications in security, defense, and disaster recovery. Radar reflections from a human can be orders of magnitude weaker than those from objects encountered in urban settings such as walls, cars, or possibly rubble after a disaster. Furthermore, these objects can act as secondary reflectors and produce multipath returns from a person. To mitigate these issues, processing of radar return data needs to be optimized for recognizing human motion features such as walking, running, or breathing. This paper presents a theoretical analysis on the modulation effects human motion has on the radar waveform and how high levels of multipath can distort these motion effects. From this analysis, an algorithm is designed and optimized for tracking human motion in heavily clutter environments. The tracking results will be used as the fundamental detection/classification tool to discriminate human targets from others by identifying human motion traits such as predictable walking patterns and periodicity in breathing rates. The theoretical formulations will be tested against simulation and measured data collected using a low power, portable see-through-the-wall radar system that could be practically deployed in real-world scenarios. Lastly, the performance of the algorithm is evaluated in a series of experiments where both a single person and multiple people are moving in an indoor, cluttered environment.
KEYWORDS: Radar, Digital signal processing, Calibration, Signal to noise ratio, Ka band, Detection and tracking algorithms, Environmental sensing, Target detection, Homeland security, Signal processing
Footprint and human trail detection in rugged all-weather environments is an important and challenging problem for perimeter security, passive surveillance and reconnaissance. To address this challenge a low-cost, wideband, frequency-modulated continuous wave (FMCW) radar operating at 33.4GHz – 35.5GHz is being developed through a Department of Homeland Security Science and Technology Directorate Phase I SBIR and has been experimentally demonstrated to be capable of detecting footprints and footprint trails on unimproved roads in an experimental setting. It uses a low-cost digital signal processor (DSP) that makes important operating parameters reconfigurable and allows for frequency sweep linearization, a key technique developed to increase footprint signal-to-noise ratio (SNR). This paper discusses the design, DSP implementation and experimental results of a low-cost FMCW radar for mobile footprint detection. A technique for wideband sweep linearization is detailed along with system performance metrics and experimental results showing receive-SNR from footprint trails in sand and on unimproved dirt roads. Results from a second stepped frequency CW (SFCW) Ka-band system are also shown, verifying the ability of both systems to detect footprints and footprint trails in an experimental setting. The results show that there is sufficient receive-SNR to detect even shallow footprints (~1cm) using a radar based detection system in Ka-band. Field experimental results focus on system proof of concept from a static position with mobile results also presented highlighting necessary improvements to both systems.
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