RE: radar detector preferences?

[Stephan Martone <smarton@luc.edu>]

- ------ =_NextPart_000_01BD429B.E20B08E0
Content-Type: text/plain; charset="us-ascii"
Content-Transfer-Encoding: quoted-printable

I just bought a Valentine 1 from Valentine research.  I have a friend =
who has had one for a while so I have seen it in action for over a year =
now.
http://www.valentine1.com/
It has a ton of features and does particularly well versus other =
detectors in the tests published in car magazines. =20
The major features in my opinion are:
1. It has two antennas.  One is facing front and the other  is facing =
the rear.  It detects X, K, Ka, and Laser.
2. It has a display that shows the direction the radar is coming from. =
Front, Side, and Rear.  I especially like watching the radar source go =
by.  The display shows front then side then rear.
3. It counts the radar sources up to 9.  For example, if you usually go =
by a convenience store and see 2 sources(the self opening doors) , then =
one day you go by and there are 3 sources (the self opening doors + 1 =
police car) you have more information to work with.=20
4. It has three levels you can use to help weed out  false alarms.  (A) =
all bogeys  (L1) Partial logic, and (L2) Full logic
5. It has a remote display that shows all of what you see on the main =
detector.  You can mount it on your steering column for instance and use =
the remote display which turns off the display on the detector off =
leaving it dark.  (Costs extra)
I could go on and on.  Perhaps you should check the website, if this =
interests you.
BTW, I am not affiliated with Valentine Research, just a fan of their =
detector.  FYI:  It is mail order only from the manufacturer so don't go =
looking for it at your local electronics store.
Stephan Martone
'97 Jetta GLX, Black 5spd=20
>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>
Zeek wrote:=20
ok my radar detector is a little old.  it's only a two band (X and K) =
and was prettly much useless in the neighboring state of LA, and while i =
know the highway patrol here in TX uses K band, i'm not sure if anyone =
here is using Ka band...
does anyone have any recommendations on a GOOD tri-band radar detector? =
i'd like something reeeealllly sensitive to the K and Ka bands and weeds =
out the useless X band if possible.  laser detection would be an added =
bonus... but realistically if they've got laser they can get you in like =
two seconds so just knowing they're shooting at you doesn't help. you're =
gonna find out when you see the flashing lights anyway!

BTW- breakin period is officially over :) i've got like 2300 miles now.  =
was playing with a Q45 today.... we weren't racing- i still had *plenty* =
of pull left- but we were both going zoooom! like 100-125 most of the =
way. first i let him lead for like ahundred miles or so and i followed =
at a safe distance figuring he could take any radar action and i'd go =
scott free- but then i smoked by him and for another hundred miles he =
followed... i didn't get the impression he was struggling to keep up- =
what's under these guys hoods? anyway i'm sure my money to power ratio =
is much better.... as well as my money to driver satisfaction ratio to =
boot. screw luxury.  real nice guy, though (older gentleman) when i =
exited i waved through my 'roof (i love doing that) and he =
waved/smiled...
oh what's better than waving is when you want to flip off some asshole =
and the sunroof's closed and he's watching- deliberately opening up =
sunroof- flipping off- closing sunroof.  ooooo that makes em so mad!

_____________________
spank me hard- REAL hard=20



- ------ =_NextPart_000_01BD429B.E20B08E0
Content-Type: application/ms-tnef
Content-Transfer-Encoding: base64
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==

- ------ =_NextPart_000_01BD429B.E20B08E0--