With the repair manual circuit diagrams in hand, it was no problem to find the GPS RX and TX lines that were being broken out to the external connector. Unfortunately, the radio’s electronics are all 5 volts and the GPS module [Selim] wanted to use was only 3.3 V. So he came up with a small PCB that included not only the voltage regulator to power the GPS module, but also some voltage-dividers to level shift those signals.
Since the Kenwood TM-D710a was already designed to accept a GPS upgrade module, he just needed to change some configuration options in the radio’s menus for it to see the new hardware. Technically the project was done at this point, but since there was still room in the case and he had a GPS module spitting out NMEA sentences, [Selim] tacked on a common Bluetooth serial module so he could see the position information on his smartphone. With an application like APRSdroid, he now has a nice moving map display using the position pulled from the radio’s GPS.
The rise of open source hardware has seen a wide variety of laborious tasks become successfully automated, saving us humans a great deal of hassle. Suffice to say, some chores are easier to automate than others. Take the classic case of a harmless autonomous vacuum cleaner that can be pretty dumb, bumping around the place to detect the perimeter as it traverses the room blindly with a pre-programmed sweeping pattern.
Now in principle, this idea could be extended to mowing your lawn. But would you really want a high speed rotating blade running rampant as it aimlessly ventures outside the perimeter of your lawn? The Sunray update to the Ardumower autonomous lawn mower project has solved this problem without invoking the need to lay down an actual perimeter wire. As standard consumer grade GPS is simply not accurate enough, so the solution involves implementing your very own RTK-GPS hardware and an accompanying base station, introducing centimeter-level accuracy to your mowing jobs.
RTK-GPS, also known as Carrier Phase Enhanced GPS, improves the accuracy of standard GPS by measuring the error in the signal using a reference receiver whose position is known accurately. This information is then relayed to the Ardumower board over a radio link, so that it could tweak its position accordingly. Do you need the ability to carve emojis into your lawn? No. But you could have it anyway. If that’s not enough to kick off the autonomous lawnmower revolution, we don’t know what is.
You’ve built a brand new project, and it’s a wonderful little thing that’s out and about in the world. The only problem is, you need to know its location to a decent degree of accuracy. Thankfully, GPS is a thing! With an off-the-shelf module, it’s possible to get all the location data you could possibly need. But how do you go about it, and what parts are the right ones for your application? For the answers to these questions, read on! Continue reading “How To Choose The Right GPS Module For Your Project”→
[Mike]’s investigation combined several avenues of investigation. In terms of decoding live radio signals, he selected a KiwiSDR software defined radio. Combined with a Digilent Nexys 2 FPGA, it was now possible to get live data off the air and into the PC quickly for decoding. In concert with this, [Mike] used a sample of raw GPS data captured in Nottingham, UK in order to test his code. After much experimentation, [Mike] was able to get the data decoded with 700 lines of C code. Decoding three minutes worth of data took all night, but further development allowed things to be sped up over 200 times. For the curious, the code is up on Github to convert raw ADC samples into actual location fixes.
[Jay Doscher] shares a quick GPS project he designed and completed over a weekend. The device is called the CLUE Tracker and has simple goals: it shows a user their current location, but also provides a compass heading and distance to a target point. The idea is a little like geocaching, in that a user is pointed to a destination but must find their own way there. There’s a 3D printed enclosure, and as a bonus, there is no soldering required.
[Jay] did a nice job of commenting and documenting the code, so this could make a great introductory CircuitPython project. No soldering is required, which makes it a little easier to re-use the parts in other projects later. This helps to offset costs for hackers on a budget.
The fact that a device like this can be an afternoon or weekend project is a testament to the fact that times have never been better for hobbyists when it comes to hardware. CircuitPython is also a fast-growing tool, and projects like this can help make it easy and fun to get started.
As the Raspberry Pi in its various forms continues to flow into the wild by the thousands, it’s interesting to see its user base expand outside beyond the hacker communities. One group of people who’ve also started taking a liking to it is sailing enthusiasts. [James Conger] is one such sailor, and he built his own AIS enabled chart plotter for a fraction of the price of comparable commercial units.
Automatic Identification System (AIS) is a GPS tracking system that uses transponders to transmit a ship’s position data to other ships or receiver stations in an area. This is used for collision avoidance and by authorities (and hobbyists) to keep an eye on shipping traffic, and allow for stricken vessels to be found easily. [James]’ DIY chart plotter overlays the received AIS data over marine charts on a nice big display. A Raspberry Pi 3B+, AIS Receiver Hat, USB GPS dongle and a makes up the core of the system. The entire setup cost about $350. The Pi runs OpenCPN, an open source chart plotter and navigation software package that [John] says is rivals most commercial software. As most Pi users will know the SD card is often a weak link, so it’s probably worth having a backup SD card with all the software already installed just in case it fails during a voyage.
If your only experience with Garmins is from that one rental car a few years back, it may surprise you that some of them, mostly the handheld outdoor units, allow custom maps. This sounds cool until you find out the limitations. Unless you upgrade to premium, it doesn’t allow map files larger than 3MB. What’s worse, it will choke the resolution of maps larger than one megapixel. Well, bust out your virtual hiking boots, because [facklere]’s gonna take you down the trail of DIY digital cartography.
You can use any map you want as long as its not completely fictional (although wandering the maps of middle-earth would be a fun hack on top of this one). Your map can be paper, PDF, or parchment; it just has to be converted to JPEG. The map [facklere] wanted to use was a huge PDF, so as a bonus, he shows how to get from PDF to JPEG in GIMP. Then comes the fiddly part — rooting the map in reality by overlaying it on real roads using Google Earth.
You’ve still got a huge map. Now what? The secret sauce is tiling. [facklere] used KMZfactory, a free map editor for Garmin maps that goes the extra mile to split the tiles for you, keeping them under the 1MP limit. Once that’s done, just upload it to your unit and hit the road.