A Real-Time Capable Software-Defined Receiver Using GPU for Adaptive Anti-Jam GPS Sensors

Due to their weak received signal power, Global Positioning System (GPS) signals are vulnerable to radio frequency interference. Adaptive beam and null steering of the gain pattern of a GPS antenna array can significantly increase the resistance of GPS sensors to signal interference and jamming. Since adaptive array processing requires intensive computational power, beamsteering GPS receivers were usually implemented using hardware such as field-programmable gate arrays (FPGAs). However, a software implementation using general-purpose processors is much more desirable because of its flexibility and cost effectiveness. This paper presents a GPS software-defined radio (SDR) with adaptive beamsteering capability for anti-jam applications. The GPS SDR design is based on an optimized desktop parallel processing architecture using a quad-core Central Processing Unit (CPU) coupled with a new generation Graphics Processing Unit (GPU) having massively parallel processors. This GPS SDR demonstrates sufficient computational capability to support a four-element antenna array and future GPS L5 signal processing in real time. After providing the details of our design and optimization schemes for future GPU-based GPS SDR developments, the jamming resistance of our GPS SDR under synthetic wideband jamming is presented. Since the GPS SDR uses commercial-off-the-shelf hardware and processors, it can be easily adopted in civil GPS applications requiring anti-jam capabilities

GNSS-SDR pseudorange quality and single point positioning performance assessment

In recent years, we have witnessed a growing demand for GNSS receiver customization in terms of modification of signal acquisition, tracking, and processing strategies. Such demands may be addressed by software-defined receivers (SDRs) which refers to an ensemble of hardware and software technologies and allows re-configurable radio communication architectures. The crux of the SDRs is the replacement of the hardware components through software modules. In this paper, we assess the quality of GNSS observables acquired by SDR against the selected u-blox low-cost receiver. In the following, we investigate the performance level of single point positioning that may be reached with an ultra-low-cost SDR and compare it to that of the low-cost GNSS receiver. The signal quality assessment revealed a comparable performance in terms of carrier-to-noise density ratio and a significant out-performance of the u-blox over SDR in terms of code pseudorange noise. The experimentation in the positioning domain proved that software-defined receivers may offer a position solution with three-dimensional standard deviation error at the level of 5.2 m in a single point positioning mode that is noticeably poorer accuracy as compared to the low-cost receiver. Such results demonstrate that there is still room for SDR positioning accuracy improvement

Development of Record and Management Software for GPS/Loran Measurements

In this paper, a software implementation that records Global Positioning System (GPS) and long-range navigation (Loran) measurement data output from an integrated GPS/Loran receiver and organizes them based on time is proposed. The purpose of the developed software is to collect measurements from multiple Loran transmitter chains for performance analysis of navigation methods using Loran, and to organize the data based on time to make it easy to use them. In addition, GPS measurements are also collected and managed as ground truth data for performance analysis. The implemented software consists of three modules: recording, classification, and conversion. The recording module records raw text data streamed from the receiver, and the classification module classifies the recorded text data according to the message format. The conversion module parses the classified text data, sorts GPS and Loran measurements based on timestamp, and outputs them according to the software platform of the user to analyze the measurements. Each module of the software runs automatically without user intervention. The functionality of the implemented software was verified using GPS and Loran measurements collected over 24 h from an actual integrated GPS/Loran receiver.Comment: Submitted to ICCAS 202

Design of high‐speed software defined radar with GPU accelerator

Software defined radar (SDRadar) systems have become an important area for future radar development and are based on similar concepts to Software defined radio (SDR). Most of the processing like filtering, frequency conversion and signal generation are implemented in software. Currently, radar systems tend to have complex signal processing and operate at wider bandwidth, which means that limits on the available computational power must be considered when designing a SDRadar system. This paper presents a feasible solution to this potential limitation by accelerating the signal processing using a GPU to enable the development of a high speed SDRadar system. The developed system overcomes the limitation on the processing speed by CPU-only, and has been tested on three different SDR devices. Results show that, with GPU accelerator, the processing rate can achieve up to 80 MHz compared to 20 MHz with the CPU-only. The high speed processing makes it possible to run in real-time and process full bandwidth across the WiFi signal acquired by multiple channels. The gains made through porting the processing to the GPU moves the technology towards real-world application in various scenarios ranging from healthcare to IoT, and other applications that required significant computational processing

A Preliminary Study of Machine-Learning-Based Ranging with LTE Channel Impulse Response in Multipath Environment

Alternative navigation technology to global navigation satellite systems (GNSSs) is required for unmanned ground vehicles (UGVs) in multipath environments (such as urban areas). In urban areas, long-term evolution (LTE) signals can be received ubiquitously at high power without any additional infrastructure. We present a machine learning approach to estimate the range between the LTE base station and UGV based on the LTE channel impulse response (CIR). The CIR, which includes information of signal attenuation from the channel, was extracted from the LTE physical layer using a software-defined radio (SDR). We designed a convolutional neural network (CNN) that estimates ranges with the CIR as input. The proposed method demonstrated better ranging performance than a received signal strength indicator (RSSI)-based method during our field test.Comment: Submitted to IEEE/IEIE ICCE-Asia 202

Tactical ISR/C2 Integration with AI/ML Augmentation

NPS NRP Project PresentationNAVPLAN 2021 specifies Distributed Maritime Operations (DMO) with a tactical grid to connect distributed nodes with processing at the tactical edge to include Artificial Intelligence/Machine Learning (AI/ML) in support of Expeditionary Advanced Base Operations (EABO) and Littoral Operations in a Contested Environment (LOCE). Joint All-Domain Command and Control (JADC2) is the concept for sensor integration. However, Intelligence, Surveillance and Reconnaissance (ISR) and Command and Control (C2) hardware and software have yet to be fully defined, tools integrated, and configurations tested. This project evaluates options for ISR and C2 integration into a Common Operational Picture (COP) with AI/ML for decision support on tactical clouds in support of DMO, EABO, LOCE and JADC2 objectives.Commander, Naval Surface Forces (CNSF)U.S. Fleet Forces Command (USFF)This research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

Penerapan Low Noise Tayloe Detector untuk High Frequency Transceiver 7 MHz Berbasis Software Defined Radio (SDR)

RINGKASAN Software define radio (SDR) adalah paradigma baru dalam desain perangkat komunikasi wireless. Teknologi SDR saat ini digunakan secara luas pada bidang telekomunikasi komersil seperti satelit komunikasi, telepon bergerak dan sangat popular digunakan pada kalangan penggiat radio amatir. SDR adalah suatu sistem radio dimana komponen-komponennya yang biasanya di bangun oleh perangkat keras (mixer, filter, modulator, demodulator dll.) telah digantikan fungsinya oleh perangkat lunak. Software defined radio saat ini sangat dikenal dikalangan komunitas radio amatir di seluruh dunia. Berbagai desain transceiver berbasis SDR yang bekerja pada band high frequency (HF) telah banyak diaplikasikan, dan berbagai perangkat lunak aplikasi SDR telah dikembangkan. Perangkat transceiver berbasis SDR digemari oleh penggiat radio amatir dikarenakan rangkaian elektronik yang sederhana dan kualitas kinerjanya yang sangat baik. Namun permasalahan yang sering dijumpai adalah nilai noise yang tinggi dan rendahnya sensitivitas dari receiver berbasis SDR. Dengan latar belakang tersebut maka pada penelitian ini akan diterapkan low noise Tayloe detector pada transceiver 7 MHz berbasis software defined radio (SDR) dengan tujuan untuk mendapatkan karakteristik low noise dan sensitivitas yang meningkat

DESAIN LOW NOISE TRANSCEIVER 7 MHZ BERBASIS SOFTWARE DEFINED RADIO (SDR)

Software defined radio (SDR) adalah paradigma baru dalam desain perangkat komunikasi wireless. Teknologi SDR saat ini digunakan secara luas pada bidang telekomunikasi komersil seperti satelit komunikasi, telepon bergerak dan banyak digunakan pada kalangan komunitas radio amatir. SDR adalah suatu sistem radio dimana komponen-komponennya yang biasanya di bangun oleh perangkat keras (mixer, filter, modulator, demodulator dll) digantikan fungsinya oleh perangkat lunak. Software defined radio saat ini sangat dikenal dikalangan komunitas radio amatir di seluruh dunia. Berbagai desain transceiver berbasis SDR yang bekerja pada band high frequency (HF) telah banyak diaplikasikan, dan berbagai perangkat lunak aplikasi SDR telah dikembangkan. Perangkat transceiver berbasis SDR digemari oleh komunitas radio amatir dikarenakan rangkaian elektroniknya yang sederhana. Namun dari kelebihan tersebut muncul permasalahan yang sering dijumpai adalah noise pada penerima yang tinggi dan sensitivitas rendah. Dengan latar belakang permasalahan tersebut, maka pada penelitian ini dirancanglah suatu low noise transceiver 7 MHz berbasis software defined radio (SDR). Metode yang digunakan dalam mengurangi noise adalah dengan pemisahan grounding dari rangkaian digital, analog dan penguat RF serta pemilihan chip Tayloe detector yang memiliki nilai resistansi switch yang rendah yaitu 4 ohm. Berdasarkan hasil pengujian dengan menggunakan integrated circuit (IC) yang memiliki nilai resistansi switching yang rendah 4 ohm didapatkan kinerja transceiver yang lebih baik, dimana penerimaan lebih sensitive dan memiliki noise yang lebih rendah