Products reviews
Meade Polaris 50 AZ-P Telescope$39.00 to $70.00
Tags:meade, polaris, 50, az-p, telescope, | Meade ETX-80AT-TC (270 x 80mm) Telescope$245.00 to $276.00
Tags:meade, etx-80at-tc, 270, x, 80mm, telescope, | Meade A 114EQ-ASTR Telescope$129.00 to $177.00
Tags:meade, a, 114eq-astr, telescope, |
Meade LXD75AR-6 Telescope

Diffraction-Limited Optics Meades Schmidt-Newtonian and Schmidt-Cassegrain optics yield pinpoint stellar images over an extremely wide field-of-view with only half the coma of standard Newtonians of the same focal ratio.
Tasco 49070800 Spacestation(r) 70az Refractor Telescope (600 x 70mm)

With its 70mm lens and all the bells and whistles, the Tasco Spacestation 70AZ is ideal for both the beginner and amateur astronomer.
Bushnell NorthStar 78-8890 (300 x 90mm) Telescope

The NorthStar® telescopes offer amateur astronomers state-of-the-art computer-driven location and tracking capability with simple, push-button control. With a built-in data base of 20,000 celestial objects, you simply call up your target on the hand-held control module, enter a simple "Go To" command and the NorthStar computer does the rest. Once locked on, tracking the object for prolonged viewing is automatic. The innovative RVO (Real Voice Output) feature provides a fun, interactive way to explore the night sky. The remote, hand-held control module features red, backlit push buttons and a red, illuminated LCD read-out for easy viewing without impairing your night vision. Minimize
Meade DS-2080ATS Telescope

Meade Digital Series telescopes bring microprocessor technology and the very latest in electromechanical design to the serious beginning or intermediate observer. Completely re-engineered and redesigned, Meade DS-2080AT telescopes provide extremely smooth motions in both altitude and azimuth, and, most importantly, include a fully integrated Autostar control system as standard equipment. Oversize bearings on both telescope axes of all models negate the imprecisions found universally, virtually without exception, on competing models.Minimize


