Products reviews
Celestron NexStar 114 SLT 31143 (270 x 144mm) Telescope$220.00 to $399.00
Tags:celestron, nexstar, 114, slt, 31143, 270, x, 144mm, telescope, | Celestron NexStar 6 SE (354 x 55.88mm) Telescope$790.00 to $1,100.00
Tags:celestron, nexstar, 6, se, 354, x, 55.88mm, telescope, | Celestron PowerSeeker 80 EQ (225 x 80mm) Telescope$107.00 to $160.00
Tags:celestron, powerseeker, 80, eq, 225, x, 80mm, telescope, |
Meade ETX-80AT-TC (270 x 80mm) Telescope

All of the major planets except Pluto are easily observable through Meade's brand-new 80mm (3.1) achromatic refractor telescope. You can study Saturn and its ring system; the primary cloud belts of Jupiter and its 4 major satellites; the Moonlike phases of Mercury and Venus; and much more.
Galileo FS-80 Telescope

The Galileo FS-80 reflector telescope is a great beginner's reflecting telescope. The large 80mm primary mirror cell collects 33% more light than a 60mm refracting telescope. 1.25 focus housing permits the use of larger higher quality 1.25 eyepieces. Yoke mount makes the telescope easy to manage through altitude / azimuth (Up & Down, Left & Right) movement, and altitude slow motion control rod for precision adjustmentsMinimize
Celestron NexStar 102 SLT (200 x 102mm) Telescope

The popularity of our previous short tube refractor models inspired us to go a step further with the introduction of our NexStar 102 SLT. You'll find that astronomical viewing is a delight with this large, powerful 4 telescope.
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