Publications

We discuss the challenge of managing the Multifunction Phased Array Radar (MPAR) timeline to satisfy the requirements of its multiple missions, with a particular focus on weather surveillance. This command and control (C2) function partitions the available scan time among these missions, exploits opportunities to service multiple missions simultaneously, and utilizes techniques for increasing scan rate where feasible. After reviewing the candidate MPAR architectures and relevant previous research, we describe a specific C2 framework that is consistent with a demonstrated active array architecture using overlapped subarrays to realize multiple, concurrent receive beams. Analysis of recently articulated requirements for near-airport and national-scale aircraft surveillance indicates that with this architecture, 40–60% of the MPAR scan timeline would be available for the high-fidelity weather observations currently provided by the Weather Service Radar (WSR-88D) network. We show that an appropriate use of subarray generated concurrent receive beams, in concert with previously documented, complementary techniques to increase the weather scan rate, could enable MPAR to perform full weather volume scans at a rate of 1 per minute. Published observing system simulation experiments, human-in-the-loop studies and radar-data assimilation experiments indicate that high-quality weather radar observations at this rate may significantly improve the lead time and reliability of severe weather warnings relative to current observation capabilities.

The Weather Systems Processor (WSP) is an add-on system to the Airport Surveillance Radar-9 (ASR-9) that generates wind shear detection and storm tracking products for the terminal airspace. As the original system ages and pre-purchased replacement parts in the depot are used up, it becomes increasingly problematic to procure hardware components for repairs. Thus, a technical refresh is needed to sustain WSP operations into the future. This phase of the project targets the intermediate frequency digital receiver, the radar interface module, and the digital signal processor for replacement by updated hardware platforms. At the same time, the increase in computational capability allows for an upgrade in the signal processing algorithm, which will lead to data quality improvements.

Accurate predictions of en route sector capacity are vital when analyzing the benefits of proposed new air traffic management decision-support tools or new airspace designs. Controller workload is the main determinant of sector capacity. This report describes a new workload-based capacity model that improves upon the Federal Aviation Administration’s current Monitor Alert capacity model.

A Secondary Surveillance Phased Array Radar (SSPAR) supporting terminal operations is described. Interrogation and receive techniques, antenna array configuration, signal processing, and preliminary performance are presented. SSPAR’s impact on spectrum congestion in the beacon radar band is analyzed, as are concepts for integrating SSPAR and next-generation primary radars to improve the efficiency and accuracy of aircraft and weather surveillance.

The U.S. Federal Aviation Administration is deploying Automatic Dependent Surveillance-Broadcast (ADS-B) to provide next-generation surveillance derived through down- and cross-link of global positioning satellite (GPS) navigation data. While ADS-B will be the primary future surveillance system, FAA recognizes that backup surveillance capabilities must be provided to assure that air traffic control (ATC) services can continue to be provided when individual aircraft transponders fail and during localized, short-duration GPS outages. This report describes a potential ADS-B backup capability, Secondary Surveillance Phased Array Radar or SSPAR. SSPAR will interrogate aircraft transponders and receive replies using a sparse, non-rotating array of approximately 17 omnidirectional (in azimuth) antennae. Each array element will transmit and receive independently so as to form directional transmit beams for transponder interrogation, and support high-resolution direction finding for received signals. Because each SSPAR element is independently digitized, transponder returns from all azimuths can be equipped with Traffic Alert and Collision Avoidance System (TCAS) and ADS-B avionics to reduce spectrum usage and maintain the high surveillance update rate (~1 per second) achieved by ADS-B. Recurring costs for SSPAR will be low since it involves no moving parts and the number of array channels is small. This report describes an SSPAR configuration supporting terminal operations. We consider interrogation and receive approaches, antenna array configuration, signal processing and preliminary performance analysis. An analysis of SSPAR's impact on spectrum congestion in the beacon radar band is presented, as are concepts for integrating SSPAR and next generation primary radar to improve the efficiency and accuracy of aircraft and weather surveillance.

Airspace encounter models describe encounter situations that may occur between aircraft in the airspace and are a critical component of safety assessment of sense and avoid (SAA) systems for Unmanned Aircraft Systems (UASs). Some UAS will fly in international airspace under due regard and may encounter other aircraft during these operations. In these types of encounters, the intruder aircraft is likely receiving air traffic control (ATC) services, but the UAS is not. Thus, there is a need for a due regard encounter model that can be used to generate these types of encounters. This report describes the development of a due regard encounter model. In order to build the model, Lincoln Laboratory collected data for aircraft flying in international airspace using the Enhanced Traffic Management System (ETMS) data feed that was provided by the Volpe Center. Lincoln processed these data, and extracted important features to construct the model. The model is based on Bayesian networks that represent the probabilistic relationship between variables that describe how aircraft behave. The model is used to construct random aircraft trajectories that are statistically similar to those observed in the airspace. A large collection of encounters generated from an airspace encounter model can be used to evaluate the performance of a SAA system against encounter situations representative of those expected to actually occur in the airspace. Lincoln Laboratory has previously developed several other encounter models. There is an uncorrelated encounter model that is used to generate encounters with an intruder that does not have a transponder, or between two aircraft using a Mode A code of 1200 (VFR). There is also a correlated encounter model that is used when both aircraft have a transponder and at least one aircraft is in contact with ATC. Both of these models were built from radar data collected from the National Airspace System (NAS). There is also an unconventional encounter model that is used to generate encounters with unconventional intruders such as gliders, balloons, and airships--these vehicles have different flight characteristics than conventional aircraft. The framework used to construct the due regard encounter model described in this paper is similar to the prior models. The primary difference is that a different data feed is used and the model covers encounters in international flight where the aircraft of interest is flying due regard, which were not within the scope of prior models. Separate electronic files are available from Lincoln Laboratory that contain the statistical data required to generate encounter trajectories.

En route sector capacity is determined mainly by controller workload. The operational capacity model used by the Federal Aviation Administration (FAA) provides traffic alert thresholds based entirely on hand-off workload. Its estimates are accurate for most sectors. However, it tends to over-estimate capacity in both small and large sectors because it does not account for conflicts and recurring tasks. Because of those omissions it cannot be used for accurate benefits analysis of workload-reduction initiatives, nor can it be extended to estimate capacity when hazardous weather increases the intensity of all workload types. We have previously reported on an improved model that accounts for all workload types and can be extended to handle hazardous weather. In this paper we present the results of a recent regression of that model using an extensive database of peak traffic counts for all United States en route sectors. The resulting fit quality confirms the workload basis of en route capacity. Because the model has excess degrees of freedom, the regression process returns multiple parameter combinations with nearly identical sector capacities. We analyze the impact of this ambiguity when using the model to quantify the benefits of workload reduction proposals. We also describe recent modifications to the weather-impacted version of the model to provide a more stable normalized capacity measure. We conclude with an illustration of its potential application to operational sector capacity forecasts in hazardous weather.

Developing robust collision avoidance logic that reliably prevents collision without excessive alerting is challenging due to sensor error and uncertainty in the future paths of the aircraft. Over the past few years, research has focused on the use of a computational method known as dynamic programming for producing an optimized decision logic for airborne collision avoidance. This report focuses on recent research on coordination, interoperability, and multiple-threat encounters. The methodology presented in this report results in logic that is safer and performs better than legacy TCAS. Modeling and simulation indicate that the proposed methodology can bring significant benefit to the current airspace and can support the need for safe, non-disruptive collision protection as the airspace continues to evolve.

This report provides a brief review of major risk-based modeling (RBM) approaches, with particular emphasis on how these tools can be applied during initial Next Generation Air Transportation System (NextGen) concept development and how their use can be validated. Effective safety analysis should play a role even during a new system's concept definition and development. Elements of NextGen are currently progressing through these early phases. NextGen will increasingly rely on integrating multiple systems and information together to enable improved efficiency, safety, and reduced environmental impact. Ensuring that such complex interconnected systems are developed to meet safety goals requires corresponding advances in RBM and safety assessment approaches. This report does not cover the more detailed safety analyses that must be applied to mature system concepts. Rather, the focus is on approaches for hazard identification, scoping, and coarse risk estimation for systems in the early conceptual development stage, when details on the design and operation of the system have yet to be resolved. Risk models applied is this constrained context cannot be expected to provide the same complete, quantitative results as they do for mature systems. Following a review of prior models, this report continues with recommendations for RBM development, application, validation, and coordination between NextGen efforts. Also, a discussion on safety and concept development is provided.

Measurements of signals in the 1030 and 1090 MHz frequency bands have been made by MIT Lincoln Laboratory in the last several years, previously in the Boston area and most recently in April 2011, at JFK International Airport near New York City. This JFK measurement activity was performed as a part of the Lincoln Laboratory Traffic Alert and Collision Avoidance System (TCAS) work for the Federal Aviation Administration (FAA) and is the subject of this report. This report includes: 1) Overall characteristics of the 1030/1090 MHz environments, 2) Analysis of the TCAS air-to-air coordination process, 3) Examination of 1090 MHz Extended Squitter transmissions for use in TCAS, 4) Assessment of the extent and impact of TCAS operation on the airport surface.