Publications

Range-velocity (RV) ambiguity is a source of data quality degradation common to all weather radars. Various methods have been developed in recent years to combat this problem. For example, for the new NEXRAD Open Radar Data Acquisition (ORDA) system, the primary focus for range-overlay separation has been on phase-code transmission and processing techniques. There are, however, conditions under which the phase-code method fails to separate range-overlaid signals, e.g., when the overlaid power ratio is too high or the Doppler spectra are too wide. Phase-code processing also has no intrinsic capacity for velocity dealiasing. To address these issues, Lincoln Laboratory developed an alternative RV ambiguity mitigation scheme using multiple pulse-repetition interval (multi-PRI) transmission and processing. The range-dealiasing performance of the multi-PRI approach complements the capability of the phase-code technique. It can succeed when phase-code processing fails, and where it fails, phase-code processing succeeds (e.g., when an overlaid patch of signal is continuous and extensive in the radial direction). Multi-PRI also provides velocity dealiasing. However, because the multi-PRI algorithm was constructed for the Terminal Doppler Weather Radar (TDWR) with its primary mission of short-range coverage around airports, only the capability of first-trip protection was explicitly developed. This report extends the multi-PRI technique to the recovery of Doppler data from other trips, out to the long-range surveillance limit of NEXRAD. Simulated and real weather radar data are used to demonstrate the capabilities and limitations of the technique.

As part of a broader FAA program to improve supportability, the Terminal Doppler Weather Radar (TDWR) radar data acquisition (RDA) subsystem is being replaced. For this purpose we developed an engineering prototype RDA with a scalable, open-systems hardware platform. This paper describes the design and characteristics of this new system. The dramatically increased computing power and more flexible transmitter control also enables modern signal processing algorithms to be implemented to improve the quality of the base data. Results highlighting the improved range-overlay protection provided by the new algorithms are presented.

This paper is a concept study for possible future utilization of active electronically scanned radars to provide weather and aircraft surveillance functions in U.S. airspace. If critical technology costs decrease sufficiently, multi-function phased array radars might prove to be a cost effective alternative to current surveillance radars, since the number of required radars would be reduced, and maintenance and logistics infrastructure would be consolidated. A radar configuration that provides terminal-area and long-range aircraft surveillance and weather measurement capability is described and a radar network design that replicates or exceeds current airspace coverage is presented. Key technology issues are examined, including transmit-receive elements, overlapped sub-arrays, the digital beamformer, and weather and aircraft post-processing algorithms. We conclude by discussing implications relative to future national weather and non-cooperative aircraft target surveillance needs. The U.S. Government currently operates four separate ground based surveillance radar networks supporting public and aviation-specific weather warnings and advisories, and primary or "skin paint" aircraft surveillance. The separate networks are: (i) The 10-cm wavelength NEXRAD or WSR88-D (Serafin and Wilson, 2000) national-scale weather radar network. This is managed jointly by the National Weather Service (NWS), the Federal Aviation Administration (FAA), and the Department of Defense (DoD). (ii) The 5-cm wavelength Terminal Doppler Weather Radars (TDWR) (Evans and Turnbull, 1989) deployed at large airports to detect low-altitude wind-shear phenomena. (iii) The 10-cm wavelength Airport Surveillance Radars (ASR-9 and ASR-11) (Taylor and Brunins, 1985) providing terminal area primary aircraft surveillance and vertically averaged precipitation reflectivity measurements. (iv) The 30-cm wavelength Air Route Surveillance Radars (ARSR-1, 2, 3 and 4) (Weber, 2005) that provide national-scale primary aircraft surveillance. The latter three networks are managed primarily by the FAA, although the DoD operates a limited number of ASRs and has partial responsibility for maintenance of the ARSR network. In total there are 513 of these radars in the contiguous United States (CONUS), Alaska, and Hawaii. The agencies that maintain these radars conduct various "life extension" activities that are projected to extend their operational life to approximately 2020. At this time, there are no defined programs to acquire replacement radars. The NWS and FAA have recently begun exploratory research on the capabilities and technology issues related to the use of multi-function phased array radar (MPAR) as a possible replacement approach. A key concept is that the MPAR network could provide both weather and primary aircraft surveillance, thereby reducing the total number of ground-based radars. In addition, MPAR surveillance capabilities would likely exceed those of current operational radars, for example, by providing more frequent weather volume scans and by providing vertical resolution and height estimates for primary aircraft targets. Table 1 summarizes the capabilities of current U.S. surveillance radars. These are approximations and do not fully capture variations in capability as a function, for example, of range or operating mode. A key observation is that significant variation in update rates between the aircraft and weather surveillance functions are currently achieved by using fundamentally different antenna patterns--low-gain vertical "fan beams" for aircraft surveillance that are scanned in azimuth only, versus high-gain weather radar "pencil beams" that are scanned volumetrically at much lower update rates. Note also that, if expressed in consistent units, the power-aperture products of the weather radars significantly exceed those of the ASRs and ARSRs. In the next section, we present a concept design for MPAR and demonstrate that it can simultaneously provide the measurement capabilities summarized in Table 1. In Section 3 we present an MPAR network concept that duplicates the airspace coverage provided by the current multiple radar networks. Section 4 discusses technology issues and associated cost considerations. We conclude in Section 5 by discussing implications relative to future national weather and non-cooperative aircraft target surveillance needs.

Multiple pulse-repetition interval (multi-PRI) transmission is part of an adaptive signal transmission and processing algorithm being developed to combat range-velocity (RV) ambiguity for the Terminal Doppler Weather Radar (TDWR). In Part I of this two-part paper, an adaptive clutter filtering procedure that yields low biases in the moments estimates was presented. In this part, algorithms for simultaneously providing range-overlay protection and velocity dealiasing using multi-PRI signal transmission and processing are presented. The effectiveness of the multi-PRI RV ambiguity mitigation scheme is demonstrated using simulated and real weather radar data, with excellent results. Combined with the adaptive clutter filter, this technique will be used within the larger context of an adaptive signal transmission and processing scheme in which phase-code processing will be a complementary alternative.

Multiple pulse repetition interval (multi-PRI) transmission is part of an adaptive signal transmission and processing algorithm being developed to aggressively combat range-velocity ambiguity in weather radars. In the past, operational use of multi-PRI pulse trains has been hampered due to the difficulty in clutter filtering. This paper presents finite impulse response clutter filter designs for multi-PRI signals with excellent magnitude and phase responses. These filters provide strong suppression for use on low-elevation scans and yield low biases of velocity estimates so that accurate velocity dealiasing is possible. Specifically, the filters are designed for use in the Terminal Doppler Weather Radar (TDWR) and are shown to meet base data bias requirements equivalent to the Federal Aviation Administration's specifications for the current TDWR clutter filters. Also an adaptive filter selection algorithm is proposed that bases its decision on clutter power estimated during an initial long-PRI surveillance scan. Simulations show that this adaptive algorithm yields satisfactory biases for reflectivity, velocity, and spectral width. Implementation of such a scheme would enable automatic elimination of anomalous propagation signals and constant adjustment to evolving ground clutter conditions, an improvement over the current TDWR clutter filtering system.

The Terminal Doppler Weather Radar (TDWR) radar data acquisition (RDA) subsystem is being replaced as part of a broader FAA program to improve the supportability of the system. An engineering prototype RDA has been developed with a scalable, open-systems hardware platform. With the dramatically increased computing power and more flexible transmitter control, modern signal processing algorithms can be implemented to improve the quality of the base data. Nation-wide, the most serious data quality challenge is range-velocity (RV) ambiguity. In a previous study (Cho et al., 2003) we showed that multiple pulse repetition interval (PRI) and constant-PRI phase-code processing have complementary strengths with respect to range-fold protection, and pro-posed an adaptive waveform and processing selection scheme on a radial-by-radial basis. Here we describe the scheme and give more details about the clutter filtering and velocity dealiasing algorithms to be used on the two types of signals.

The Terminal Doppler Weather Radar (TDWR) radar data acquisition (RDA) subsystem is being replaced as part of a broader FAA program to improve the supportability of the system. An engineering prototype RDA is under development that will provide a modern, open-systems hardware platform and standards-compliant software. The new platform also provides an opportunity to insert algorithms to improve the quality of existing base data products, as well as support future enhancements to the aviation weather services provided by TDWR. There are several outstanding data quality issues with the TDWR. In this paper, we focus on mitigation schemes for the range-velocity ambiguity problem that is especially severe for C-band weather radars such as the TDWR.

Range and velocity ambiguities pose significant data quality challenges for the Terminal Doppler Weather Radar (TDWR). For typical pulse repetition frequencies (PRFs) of 1-2 kHz, the radar is subject to both range-ambiguous precipitation returns and velocity aliasing. Experience shows that these are a major contributor to failures of the system's wind shear detection algorithms. Here we evaluate the degree of mitigation offered by existing phase diversity methods to these problems. Using optimized processing techniques, we analyze the performance of two particular phase codes that are best suited for application to TDWRs- random and SZ(8/64) [Sachidananda and Zrnic', [1999]- in the protection of weak-trip power, velocity, and spectral width estimates. Results from both simulated and real weather data indicate that the SZ(8/64) code generally outperforms the random code, except for protection of 1st trip from 5th trip interference. However, the SZ code estimates require a priori knowledge of out-of-trip spectral widths for censoring. This information cannot be provided adequately by a separate scan with a Pulse Repetition Frequency (PRF) low enough to unambiguously cover the entire range of detectable weather, because then the upper limit of measurable spectral width is only about 2 m/s . For this reason we conclude that SZ phase codes are not appropriate for TDWR use. For velocity ambiguity resolution, the random phase code could be transmitted at two PRFs on alternating dwells. Assuming the velocity changes little between two consecutive dwells, a Chinese remainder type of approach can be used to dealias the velocities. Strong ground clutter at close range, however, disables this scheme for gates at the beginning of the 2nd trip of the higher PRF. We offer an alternative scheme for range-velocity ambiguity mitigation: Multistaggered Pulse Processing (MSPP). Yielding excellent velocity dealiasing capabilities, the MSPP method should also provide protection from patchy, small-scale out-of-trip weather. To obtain maximum performance in both range and velocity dealiasing, we suggest that information from the initial low-PRF scan be used to decide the best waveform to transmit in the following scan-random phase code with alternating-dwell PRFs or MSPP. Such an adaptive approach presages future developments in weather radar, for example electronically scanned arrays allow selective probing of relevant weather events.